Overview

Dataset statistics

Number of variables58
Number of observations1000
Missing cells14114
Missing cells (%)24.3%
Total size in memory3.8 MiB
Average record size in memory3.8 KiB

Variable types

Numeric1
Text53
Unsupported3
URL1

Alerts

vendor_dba has 873 (87.3%) missing valuesMissing
email has 1000 (100.0%) missing valuesMissing
cert_renewal_date has 270 (27.0%) missing valuesMissing
address2 has 618 (61.8%) missing valuesMissing
mailingaddress2 has 607 (60.7%) missing valuesMissing
website has 283 (28.3%) missing valuesMissing
date_of_establishment has 84 (8.4%) missing valuesMissing
aggregate_bonding_limit has 890 (89.0%) missing valuesMissing
signatory_to_union_contracts has 931 (93.1%) missing valuesMissing
types_of_construction_projects_performed has 1000 (100.0%) missing valuesMissing
name_of_client_job_exp_1 has 42 (4.2%) missing valuesMissing
largest_value_of_contract has 52 (5.2%) missing valuesMissing
percent_self_performed_job_exp_1 has 97 (9.7%) missing valuesMissing
date_of_work_job_exp_1 has 42 (4.2%) missing valuesMissing
description_of_work_job_exp_1 has 43 (4.3%) missing valuesMissing
name_of_client_job_exp_2 has 211 (21.1%) missing valuesMissing
value_of_contract_job_exp_2 has 227 (22.7%) missing valuesMissing
percent_self_performed_job_exp_2 has 262 (26.2%) missing valuesMissing
date_of_work_job_exp_2 has 211 (21.1%) missing valuesMissing
description_of_work_job_exp_2 has 211 (21.1%) missing valuesMissing
name_of_client_job_exp_3 has 328 (32.8%) missing valuesMissing
value_of_contract_job_exp_3 has 344 (34.4%) missing valuesMissing
percent_self_performed_job_exp_3 has 387 (38.7%) missing valuesMissing
date_of_work_job_exp_3 has 328 (32.8%) missing valuesMissing
description_of_work_job_exp_3 has 328 (32.8%) missing valuesMissing
capacity_building_programs has 1000 (100.0%) missing valuesMissing
borough has 380 (38.0%) missing valuesMissing
latitude has 380 (38.0%) missing valuesMissing
longitude has 380 (38.0%) missing valuesMissing
community_board has 380 (38.0%) missing valuesMissing
council_district has 380 (38.0%) missing valuesMissing
bin has 387 (38.7%) missing valuesMissing
bbl has 387 (38.7%) missing valuesMissing
census_tract_2020_ has 380 (38.0%) missing valuesMissing
neighborhood_tabulation_area_nta_2020_ has 380 (38.0%) missing valuesMissing
0 has unique valuesUnique
account_number has unique valuesUnique
vendor_formal_name has unique valuesUnique
email is an unsupported type, check if it needs cleaning or further analysisUnsupported
types_of_construction_projects_performed is an unsupported type, check if it needs cleaning or further analysisUnsupported
capacity_building_programs is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-09 23:12:18.451559
Analysis finished2023-12-09 23:12:21.449168
Duration3 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

0
Real number (ℝ)

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean500.5
Minimum1
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2023-12-09T23:12:21.568027image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile50.95
Q1250.75
median500.5
Q3750.25
95-th percentile950.05
Maximum1000
Range999
Interquartile range (IQR)499.5

Descriptive statistics

Standard deviation288.8194361
Coefficient of variation (CV)0.5770618104
Kurtosis-1.2
Mean500.5
Median Absolute Deviation (MAD)250
Skewness0
Sum500500
Variance83416.66667
MonotonicityStrictly increasing
2023-12-09T23:12:21.728592image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
672 1
 
0.1%
659 1
 
0.1%
660 1
 
0.1%
661 1
 
0.1%
662 1
 
0.1%
663 1
 
0.1%
664 1
 
0.1%
665 1
 
0.1%
666 1
 
0.1%
Other values (990) 990
99.0%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
ValueCountFrequency (%)
1000 1
0.1%
999 1
0.1%
998 1
0.1%
997 1
0.1%
996 1
0.1%

account_number
Text

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size60.9 KiB
2023-12-09T23:12:22.171378image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.258
Min length2

Characters and Unicode

Total characters5258
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1000 ?
Unique (%)100.0%

Sample

1st row311147
2nd row357418
3rd row331157
4th row10003
5th row342721
ValueCountFrequency (%)
10660 1
 
0.1%
102062 1
 
0.1%
326940 1
 
0.1%
10539 1
 
0.1%
330490 1
 
0.1%
7109 1
 
0.1%
10185 1
 
0.1%
10675 1
 
0.1%
287182 1
 
0.1%
309818 1
 
0.1%
Other values (990) 990
99.0%
2023-12-09T23:12:22.746167image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 939
17.9%
0 870
16.5%
3 770
14.6%
2 467
8.9%
6 443
8.4%
4 425
8.1%
5 400
7.6%
7 325
 
6.2%
9 313
 
6.0%
8 306
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5258
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 939
17.9%
0 870
16.5%
3 770
14.6%
2 467
8.9%
6 443
8.4%
4 425
8.1%
5 400
7.6%
7 325
 
6.2%
9 313
 
6.0%
8 306
 
5.8%

Most occurring scripts

ValueCountFrequency (%)
Common 5258
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 939
17.9%
0 870
16.5%
3 770
14.6%
2 467
8.9%
6 443
8.4%
4 425
8.1%
5 400
7.6%
7 325
 
6.2%
9 313
 
6.0%
8 306
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5258
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 939
17.9%
0 870
16.5%
3 770
14.6%
2 467
8.9%
6 443
8.4%
4 425
8.1%
5 400
7.6%
7 325
 
6.2%
9 313
 
6.0%
8 306
 
5.8%

vendor_formal_name
Text

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size79.7 KiB
2023-12-09T23:12:23.135598image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length63
Median length43
Mean length24.447
Min length6

Characters and Unicode

Total characters24447
Distinct characters76
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1000 ?
Unique (%)100.0%

Sample

1st row#1Pho Inc
2nd row#NAME?
3rd row024 Inc
4th row1 Call Building Maintenance Corp.
5th row1 Of A Kind Home Health Care L.L.C.
ValueCountFrequency (%)
inc 385
 
10.4%
llc 294
 
7.9%
corp 109
 
2.9%
86
 
2.3%
construction 71
 
1.9%
services 67
 
1.8%
a 64
 
1.7%
consulting 50
 
1.3%
group 45
 
1.2%
all 36
 
1.0%
Other values (1405) 2503
67.5%
2023-12-09T23:12:23.699218image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2712
 
11.1%
n 1746
 
7.1%
e 1483
 
6.1%
i 1276
 
5.2%
r 1264
 
5.2%
o 1142
 
4.7%
t 1126
 
4.6%
A 1115
 
4.6%
c 1102
 
4.5%
a 1070
 
4.4%
Other values (66) 10411
42.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 14853
60.8%
Uppercase Letter 5581
 
22.8%
Space Separator 2712
 
11.1%
Other Punctuation 995
 
4.1%
Decimal Number 262
 
1.1%
Dash Punctuation 36
 
0.1%
Math Symbol 6
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 1746
11.8%
e 1483
10.0%
i 1276
8.6%
r 1264
8.5%
o 1142
 
7.7%
t 1126
 
7.6%
c 1102
 
7.4%
a 1070
 
7.2%
s 891
 
6.0%
l 810
 
5.5%
Other values (16) 2943
19.8%
Uppercase Letter
ValueCountFrequency (%)
A 1115
20.0%
C 913
16.4%
L 764
13.7%
I 532
9.5%
S 374
 
6.7%
P 227
 
4.1%
E 218
 
3.9%
R 171
 
3.1%
N 170
 
3.0%
T 169
 
3.0%
Other values (16) 928
16.6%
Decimal Number
ValueCountFrequency (%)
1 57
21.8%
0 36
13.7%
4 33
12.6%
2 32
12.2%
3 29
11.1%
5 18
 
6.9%
7 17
 
6.5%
8 15
 
5.7%
9 14
 
5.3%
6 11
 
4.2%
Other Punctuation
ValueCountFrequency (%)
. 524
52.7%
, 352
35.4%
& 98
 
9.8%
' 14
 
1.4%
# 2
 
0.2%
! 2
 
0.2%
/ 1
 
0.1%
? 1
 
0.1%
: 1
 
0.1%
Space Separator
ValueCountFrequency (%)
2712
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Math Symbol
ValueCountFrequency (%)
+ 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20434
83.6%
Common 4013
 
16.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 1746
 
8.5%
e 1483
 
7.3%
i 1276
 
6.2%
r 1264
 
6.2%
o 1142
 
5.6%
t 1126
 
5.5%
A 1115
 
5.5%
c 1102
 
5.4%
a 1070
 
5.2%
C 913
 
4.5%
Other values (42) 8197
40.1%
Common
ValueCountFrequency (%)
2712
67.6%
. 524
 
13.1%
, 352
 
8.8%
& 98
 
2.4%
1 57
 
1.4%
0 36
 
0.9%
- 36
 
0.9%
4 33
 
0.8%
2 32
 
0.8%
3 29
 
0.7%
Other values (14) 104
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24447
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2712
 
11.1%
n 1746
 
7.1%
e 1483
 
6.1%
i 1276
 
5.2%
r 1264
 
5.2%
o 1142
 
4.7%
t 1126
 
4.6%
A 1115
 
4.6%
c 1102
 
4.5%
a 1070
 
4.4%
Other values (66) 10411
42.6%

vendor_dba
Text

MISSING 

Distinct126
Distinct (%)99.2%
Missing873
Missing (%)87.3%
Memory size36.8 KiB
2023-12-09T23:12:24.062582image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length29
Mean length18.76377953
Min length3

Characters and Unicode

Total characters2383
Distinct characters60
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique125 ?
Unique (%)98.4%

Sample

1st rowZenyai
2nd rowKilduff Underground Engineering, Inc.
3rd rowWBE NYC
4th rowA La Fresca
5th rowAigner Chocolates
ValueCountFrequency (%)
9
 
2.5%
group 6
 
1.7%
a 5
 
1.4%
solutions 5
 
1.4%
security 5
 
1.4%
new 5
 
1.4%
services 5
 
1.4%
associates 4
 
1.1%
inc 4
 
1.1%
york 4
 
1.1%
Other values (270) 306
85.5%
2023-12-09T23:12:24.574258image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
231
 
9.7%
e 193
 
8.1%
r 146
 
6.1%
n 144
 
6.0%
o 141
 
5.9%
t 126
 
5.3%
a 125
 
5.2%
i 122
 
5.1%
s 106
 
4.4%
A 85
 
3.6%
Other values (50) 964
40.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1622
68.1%
Uppercase Letter 498
 
20.9%
Space Separator 231
 
9.7%
Other Punctuation 26
 
1.1%
Decimal Number 3
 
0.1%
Math Symbol 2
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 193
11.9%
r 146
 
9.0%
n 144
 
8.9%
o 141
 
8.7%
t 126
 
7.8%
a 125
 
7.7%
i 122
 
7.5%
s 106
 
6.5%
l 72
 
4.4%
c 71
 
4.4%
Other values (16) 376
23.2%
Uppercase Letter
ValueCountFrequency (%)
A 85
17.1%
S 59
11.8%
C 43
 
8.6%
E 33
 
6.6%
I 28
 
5.6%
T 27
 
5.4%
P 23
 
4.6%
M 22
 
4.4%
L 20
 
4.0%
N 20
 
4.0%
Other values (14) 138
27.7%
Other Punctuation
ValueCountFrequency (%)
. 9
34.6%
& 8
30.8%
, 4
15.4%
' 3
 
11.5%
/ 2
 
7.7%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
4 1
33.3%
Space Separator
ValueCountFrequency (%)
231
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2120
89.0%
Common 263
 
11.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 193
 
9.1%
r 146
 
6.9%
n 144
 
6.8%
o 141
 
6.7%
t 126
 
5.9%
a 125
 
5.9%
i 122
 
5.8%
s 106
 
5.0%
A 85
 
4.0%
l 72
 
3.4%
Other values (40) 860
40.6%
Common
ValueCountFrequency (%)
231
87.8%
. 9
 
3.4%
& 8
 
3.0%
, 4
 
1.5%
' 3
 
1.1%
+ 2
 
0.8%
2 2
 
0.8%
/ 2
 
0.8%
- 1
 
0.4%
4 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2383
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
231
 
9.7%
e 193
 
8.1%
r 146
 
6.1%
n 144
 
6.0%
o 141
 
5.9%
t 126
 
5.3%
a 125
 
5.2%
i 122
 
5.1%
s 106
 
4.4%
A 85
 
3.6%
Other values (50) 964
40.5%
Distinct749
Distinct (%)74.9%
Missing0
Missing (%)0.0%
Memory size61.8 KiB
2023-12-09T23:12:24.983745image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length14
Mean length6.087
Min length2

Characters and Unicode

Total characters6087
Distinct characters59
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique608 ?
Unique (%)60.8%

Sample

1st rowAlbert
2nd rowTodd
3rd rowGena
4th rowLorris
5th rowAndrea
ValueCountFrequency (%)
anthony 8
 
0.8%
ann 7
 
0.7%
jennifer 7
 
0.7%
muhammad 7
 
0.7%
andrew 7
 
0.7%
maria 7
 
0.7%
amy 6
 
0.6%
michael 6
 
0.6%
anne 6
 
0.6%
jose 6
 
0.6%
Other values (735) 955
93.4%
2023-12-09T23:12:25.539608image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 815
 
13.4%
e 559
 
9.2%
n 543
 
8.9%
i 446
 
7.3%
r 386
 
6.3%
l 318
 
5.2%
A 263
 
4.3%
o 251
 
4.1%
h 204
 
3.4%
t 179
 
2.9%
Other values (49) 2123
34.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4864
79.9%
Uppercase Letter 1182
 
19.4%
Space Separator 22
 
0.4%
Open Punctuation 5
 
0.1%
Close Punctuation 5
 
0.1%
Dash Punctuation 4
 
0.1%
Other Punctuation 4
 
0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 815
16.8%
e 559
11.5%
n 543
11.2%
i 446
9.2%
r 386
 
7.9%
l 318
 
6.5%
o 251
 
5.2%
h 204
 
4.2%
t 179
 
3.7%
d 177
 
3.6%
Other values (16) 986
20.3%
Uppercase Letter
ValueCountFrequency (%)
A 263
22.3%
M 110
 
9.3%
S 91
 
7.7%
J 89
 
7.5%
R 64
 
5.4%
L 55
 
4.7%
D 54
 
4.6%
N 49
 
4.1%
C 48
 
4.1%
E 43
 
3.6%
Other values (16) 316
26.7%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
' 1
 
25.0%
Space Separator
ValueCountFrequency (%)
22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Modifier Symbol
ValueCountFrequency (%)
´ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6046
99.3%
Common 41
 
0.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 815
 
13.5%
e 559
 
9.2%
n 543
 
9.0%
i 446
 
7.4%
r 386
 
6.4%
l 318
 
5.3%
A 263
 
4.3%
o 251
 
4.2%
h 204
 
3.4%
t 179
 
3.0%
Other values (42) 2082
34.4%
Common
ValueCountFrequency (%)
22
53.7%
( 5
 
12.2%
) 5
 
12.2%
- 4
 
9.8%
. 3
 
7.3%
' 1
 
2.4%
´ 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6086
> 99.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 815
 
13.4%
e 559
 
9.2%
n 543
 
8.9%
i 446
 
7.3%
r 386
 
6.3%
l 318
 
5.2%
A 263
 
4.3%
o 251
 
4.1%
h 204
 
3.4%
t 179
 
2.9%
Other values (48) 2122
34.9%
None
ValueCountFrequency (%)
´ 1
100.0%
Distinct884
Distinct (%)88.5%
Missing1
Missing (%)0.1%
Memory size62.3 KiB
2023-12-09T23:12:26.013111image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length36
Median length19
Mean length6.726726727
Min length2

Characters and Unicode

Total characters6720
Distinct characters57
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique819 ?
Unique (%)82.0%

Sample

1st rowJethanamest
2nd rowKilduff
3rd rowSurphlis
4th rowAlleyne
5th rowDavid
ValueCountFrequency (%)
singh 15
 
1.5%
williams 9
 
0.9%
khan 5
 
0.5%
smith 5
 
0.5%
patel 5
 
0.5%
gonzalez 5
 
0.5%
torres 5
 
0.5%
de 5
 
0.5%
perez 4
 
0.4%
jr 4
 
0.4%
Other values (880) 968
94.0%
2023-12-09T23:12:26.620783image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 731
 
10.9%
e 552
 
8.2%
r 468
 
7.0%
i 462
 
6.9%
n 458
 
6.8%
o 442
 
6.6%
l 346
 
5.1%
s 274
 
4.1%
t 223
 
3.3%
h 213
 
3.2%
Other values (47) 2551
38.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5369
79.9%
Uppercase Letter 1268
 
18.9%
Space Separator 32
 
0.5%
Dash Punctuation 29
 
0.4%
Other Punctuation 22
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 731
13.6%
e 552
10.3%
r 468
 
8.7%
i 462
 
8.6%
n 458
 
8.5%
o 442
 
8.2%
l 346
 
6.4%
s 274
 
5.1%
t 223
 
4.2%
h 213
 
4.0%
Other values (16) 1200
22.4%
Uppercase Letter
ValueCountFrequency (%)
A 129
 
10.2%
S 111
 
8.8%
M 100
 
7.9%
C 90
 
7.1%
B 73
 
5.8%
P 70
 
5.5%
R 67
 
5.3%
L 67
 
5.3%
G 59
 
4.7%
E 59
 
4.7%
Other values (16) 443
34.9%
Other Punctuation
ValueCountFrequency (%)
. 11
50.0%
, 8
36.4%
' 3
 
13.6%
Space Separator
ValueCountFrequency (%)
32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6637
98.8%
Common 83
 
1.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 731
 
11.0%
e 552
 
8.3%
r 468
 
7.1%
i 462
 
7.0%
n 458
 
6.9%
o 442
 
6.7%
l 346
 
5.2%
s 274
 
4.1%
t 223
 
3.4%
h 213
 
3.2%
Other values (42) 2468
37.2%
Common
ValueCountFrequency (%)
32
38.6%
- 29
34.9%
. 11
 
13.3%
, 8
 
9.6%
' 3
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6720
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 731
 
10.9%
e 552
 
8.2%
r 468
 
7.0%
i 462
 
6.9%
n 458
 
6.8%
o 442
 
6.6%
l 346
 
5.1%
s 274
 
4.1%
t 223
 
3.3%
h 213
 
3.2%
Other values (47) 2551
38.0%
Distinct994
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size65.6 KiB
2023-12-09T23:12:26.970419image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10000
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique988 ?
Unique (%)98.8%

Sample

1st row6463879761
2nd row2019939696
3rd row3479035447
4th row3474690806
5th row7183008023
ValueCountFrequency (%)
7189229404 2
 
0.2%
2126636288 2
 
0.2%
6316175951 2
 
0.2%
7183891777 2
 
0.2%
6465094601 2
 
0.2%
7185569700 2
 
0.2%
9173742930 1
 
0.1%
9293937973 1
 
0.1%
9142588462 1
 
0.1%
9145863470 1
 
0.1%
Other values (984) 984
98.4%
2023-12-09T23:12:27.432020image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1221
12.2%
7 1190
11.9%
2 1067
10.7%
6 1028
10.3%
8 960
9.6%
4 948
9.5%
0 925
9.2%
3 909
9.1%
5 880
8.8%
9 872
8.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1221
12.2%
7 1190
11.9%
2 1067
10.7%
6 1028
10.3%
8 960
9.6%
4 948
9.5%
0 925
9.2%
3 909
9.1%
5 880
8.8%
9 872
8.7%

Most occurring scripts

ValueCountFrequency (%)
Common 10000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1221
12.2%
7 1190
11.9%
2 1067
10.7%
6 1028
10.3%
8 960
9.6%
4 948
9.5%
0 925
9.2%
3 909
9.1%
5 880
8.8%
9 872
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1221
12.2%
7 1190
11.9%
2 1067
10.7%
6 1028
10.3%
8 960
9.6%
4 948
9.5%
0 925
9.2%
3 909
9.1%
5 880
8.8%
9 872
8.7%

email
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB
Distinct998
Distinct (%)99.9%
Missing1
Missing (%)0.1%
Memory size421.2 KiB
2023-12-09T23:12:27.821578image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4738
Median length534
Mean length303.6996997
Min length5

Characters and Unicode

Total characters303396
Distinct characters100
Distinct categories15 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique997 ?
Unique (%)99.8%

Sample

1st rowZenyai Viet Cajun & Pho Restaurant is dedicated to offering real Vietnamese flavor through distinct seafood boils and pho noodle dishes.
2nd rowKilduff Underground Engineering, Inc. (KUE) is a geotechnical engineering firm specializing in tunnels, underground design, and construction management throughout North America. Serving as both a design and construction management firm, our strengths lie in our ability to be equally familiar with the design and construction aspects of underground projects.
3rd row024™ is a premium home fragrance brand that designs elevated home fragrance products that contain patented scent technology. 024™'s fragrance line eliminates common lingering odors while infusing the space with immersive and captivating scents.
4th rowOur Services include Office Cleaning Carpet cleaning,Floor Stripping and Waxing and General building Maintenance.; ; BUILDING MAINTENANCE; CARPET CLEANING; CLEANING SERVICES; JANITORIAL SERVICES
5th rowNYS Licensed Home Health Agency
ValueCountFrequency (%)
and 2691
 
6.4%
the 905
 
2.1%
of 821
 
1.9%
to 794
 
1.9%
a 701
 
1.7%
in 674
 
1.6%
services 586
 
1.4%
we 543
 
1.3%
is 485
 
1.2%
447
 
1.1%
Other values (6996) 33506
79.5%
2023-12-09T23:12:28.394297image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
41054
13.5%
e 26721
 
8.8%
i 20885
 
6.9%
n 20755
 
6.8%
a 19373
 
6.4%
t 18407
 
6.1%
o 17312
 
5.7%
s 17177
 
5.7%
r 16930
 
5.6%
c 10580
 
3.5%
Other values (90) 94202
31.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 235796
77.7%
Space Separator 41079
 
13.5%
Uppercase Letter 15312
 
5.0%
Other Punctuation 8041
 
2.7%
Decimal Number 1155
 
0.4%
Control 770
 
0.3%
Dash Punctuation 719
 
0.2%
Open Punctuation 201
 
0.1%
Close Punctuation 200
 
0.1%
Final Punctuation 70
 
< 0.1%
Other values (5) 53
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 26721
11.3%
i 20885
 
8.9%
n 20755
 
8.8%
a 19373
 
8.2%
t 18407
 
7.8%
o 17312
 
7.3%
s 17177
 
7.3%
r 16930
 
7.2%
c 10580
 
4.5%
l 10557
 
4.5%
Other values (19) 57099
24.2%
Uppercase Letter
ValueCountFrequency (%)
A 1795
 
11.7%
C 1449
 
9.5%
S 1307
 
8.5%
E 1031
 
6.7%
I 995
 
6.5%
T 933
 
6.1%
N 752
 
4.9%
P 738
 
4.8%
W 723
 
4.7%
O 686
 
4.5%
Other values (16) 4903
32.0%
Other Punctuation
ValueCountFrequency (%)
, 4449
55.3%
. 2408
29.9%
/ 290
 
3.6%
& 277
 
3.4%
: 152
 
1.9%
; 139
 
1.7%
' 94
 
1.2%
90
 
1.1%
? 55
 
0.7%
" 24
 
0.3%
Other values (7) 63
 
0.8%
Decimal Number
ValueCountFrequency (%)
0 332
28.7%
1 191
16.5%
2 177
15.3%
3 89
 
7.7%
5 77
 
6.7%
9 76
 
6.6%
4 73
 
6.3%
7 48
 
4.2%
6 47
 
4.1%
8 45
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 697
96.9%
16
 
2.2%
6
 
0.8%
Math Symbol
ValueCountFrequency (%)
+ 22
91.7%
| 1
 
4.2%
= 1
 
4.2%
Space Separator
ValueCountFrequency (%)
41054
99.9%
  25
 
0.1%
Final Punctuation
ValueCountFrequency (%)
60
85.7%
10
 
14.3%
Other Symbol
ValueCountFrequency (%)
4
80.0%
® 1
 
20.0%
Control
ValueCountFrequency (%)
770
100.0%
Open Punctuation
ValueCountFrequency (%)
( 201
100.0%
Close Punctuation
ValueCountFrequency (%)
) 200
100.0%
Initial Punctuation
ValueCountFrequency (%)
13
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 10
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 251108
82.8%
Common 52288
 
17.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 26721
 
10.6%
i 20885
 
8.3%
n 20755
 
8.3%
a 19373
 
7.7%
t 18407
 
7.3%
o 17312
 
6.9%
s 17177
 
6.8%
r 16930
 
6.7%
c 10580
 
4.2%
l 10557
 
4.2%
Other values (45) 72411
28.8%
Common
ValueCountFrequency (%)
41054
78.5%
, 4449
 
8.5%
. 2408
 
4.6%
770
 
1.5%
- 697
 
1.3%
0 332
 
0.6%
/ 290
 
0.6%
& 277
 
0.5%
( 201
 
0.4%
) 200
 
0.4%
Other values (35) 1610
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 303145
99.9%
Punctuation 195
 
0.1%
None 52
 
< 0.1%
Letterlike Symbols 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
41054
13.5%
e 26721
 
8.8%
i 20885
 
6.9%
n 20755
 
6.8%
a 19373
 
6.4%
t 18407
 
6.1%
o 17312
 
5.7%
s 17177
 
5.7%
r 16930
 
5.6%
c 10580
 
3.5%
Other values (76) 93951
31.0%
Punctuation
ValueCountFrequency (%)
90
46.2%
60
30.8%
16
 
8.2%
13
 
6.7%
10
 
5.1%
6
 
3.1%
None
ValueCountFrequency (%)
  25
48.1%
· 16
30.8%
¿ 4
 
7.7%
ç 3
 
5.8%
é 2
 
3.8%
à 1
 
1.9%
® 1
 
1.9%
Letterlike Symbols
ValueCountFrequency (%)
4
100.0%
Distinct6
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size59.7 KiB
2023-12-09T23:12:28.565632image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length3
Mean length4.012
Min length3

Characters and Unicode

Total characters4012
Distinct characters6
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st rowMBE
2nd rowMBE
3rd rowMBE,WBE
4th rowMBE
5th rowMBE,WBE
ValueCountFrequency (%)
mbe 478
47.8%
wbe 270
27.0%
mbe,wbe 248
24.8%
mbe,ebe 2
 
0.2%
mbe,wbe,ebe 1
 
0.1%
mbe,lbe 1
 
0.1%
2023-12-09T23:12:28.871918image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 1256
31.3%
B 1253
31.2%
M 730
18.2%
W 519
12.9%
, 253
 
6.3%
L 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3759
93.7%
Other Punctuation 253
 
6.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 1256
33.4%
B 1253
33.3%
M 730
19.4%
W 519
13.8%
L 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
, 253
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3759
93.7%
Common 253
 
6.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 1256
33.4%
B 1253
33.3%
M 730
19.4%
W 519
13.8%
L 1
 
< 0.1%
Common
ValueCountFrequency (%)
, 253
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4012
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 1256
31.3%
B 1253
31.2%
M 730
18.2%
W 519
12.9%
, 253
 
6.3%
L 1
 
< 0.1%

cert_renewal_date
Text

MISSING 

Distinct134
Distinct (%)18.4%
Missing270
Missing (%)27.0%
Memory size58.7 KiB
2023-12-09T23:12:29.172709image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length32
Median length9
Mean length13.30821918
Min length8

Characters and Unicode

Total characters9715
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)1.6%

Sample

1st row10/31/2025
2nd row7/31/2025
3rd row04/30/2026;04/30/2026
4th row3/31/2026
5th row03/31/2027;03/31/2027
ValueCountFrequency (%)
6/30/2024 22
 
3.0%
6/30/2026 17
 
2.3%
10/31/2024 15
 
2.1%
4/30/2028 12
 
1.6%
2/29/2024 12
 
1.6%
5/31/2028 12
 
1.6%
8/31/2025 12
 
1.6%
11/30/2026 11
 
1.5%
3/31/2024 11
 
1.5%
7/31/2025 11
 
1.5%
Other values (124) 595
81.5%
2023-12-09T23:12:29.601607image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2202
22.7%
/ 1966
20.2%
0 1807
18.6%
3 1048
10.8%
1 924
9.5%
8 331
 
3.4%
4 327
 
3.4%
6 271
 
2.8%
; 253
 
2.6%
7 227
 
2.3%
Other values (2) 359
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7496
77.2%
Other Punctuation 2219
 
22.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2202
29.4%
0 1807
24.1%
3 1048
14.0%
1 924
12.3%
8 331
 
4.4%
4 327
 
4.4%
6 271
 
3.6%
7 227
 
3.0%
5 225
 
3.0%
9 134
 
1.8%
Other Punctuation
ValueCountFrequency (%)
/ 1966
88.6%
; 253
 
11.4%

Most occurring scripts

ValueCountFrequency (%)
Common 9715
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2202
22.7%
/ 1966
20.2%
0 1807
18.6%
3 1048
10.8%
1 924
9.5%
8 331
 
3.4%
4 327
 
3.4%
6 271
 
2.8%
; 253
 
2.6%
7 227
 
2.3%
Other values (2) 359
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9715
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2202
22.7%
/ 1966
20.2%
0 1807
18.6%
3 1048
10.8%
1 924
9.5%
8 331
 
3.4%
4 327
 
3.4%
6 271
 
2.8%
; 253
 
2.6%
7 227
 
2.3%
Other values (2) 359
 
3.7%
Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size63.1 KiB
2023-12-09T23:12:29.787412image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length12
Median length5
Mean length7.442
Min length5

Characters and Unicode

Total characters7442
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowASIAN
2nd rowHISPANIC
3rd rowBLACK
4th rowBLACK
5th rowBLACK
ValueCountFrequency (%)
black 299
29.9%
non-minority 270
27.0%
asian 247
24.7%
hispanic 184
18.4%
2023-12-09T23:12:30.098729image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1241
16.7%
I 1155
15.5%
A 977
13.1%
O 540
 
7.3%
C 483
 
6.5%
S 431
 
5.8%
B 299
 
4.0%
L 299
 
4.0%
K 299
 
4.0%
- 270
 
3.6%
Other values (6) 1448
19.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 7172
96.4%
Dash Punctuation 270
 
3.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1241
17.3%
I 1155
16.1%
A 977
13.6%
O 540
7.5%
C 483
 
6.7%
S 431
 
6.0%
B 299
 
4.2%
L 299
 
4.2%
K 299
 
4.2%
M 270
 
3.8%
Other values (5) 1178
16.4%
Dash Punctuation
ValueCountFrequency (%)
- 270
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7172
96.4%
Common 270
 
3.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1241
17.3%
I 1155
16.1%
A 977
13.6%
O 540
7.5%
C 483
 
6.7%
S 431
 
6.0%
B 299
 
4.2%
L 299
 
4.2%
K 299
 
4.2%
M 270
 
3.8%
Other values (5) 1178
16.4%
Common
ValueCountFrequency (%)
- 270
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7442
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1241
16.7%
I 1155
15.5%
A 977
13.1%
O 540
 
7.3%
C 483
 
6.5%
S 431
 
5.8%
B 299
 
4.0%
L 299
 
4.0%
K 299
 
4.0%
- 270
 
3.6%
Other values (6) 1448
19.5%
Distinct990
Distinct (%)99.3%
Missing3
Missing (%)0.3%
Memory size73.4 KiB
2023-12-09T23:12:30.559074image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length44
Median length32
Mean length18.1444333
Min length8

Characters and Unicode

Total characters18090
Distinct characters68
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique983 ?
Unique (%)98.6%

Sample

1st row208 Grand Street
2nd row9 Globe Ct
3rd row120 Elgar Place
4th row946 Atlantic Ave
5th row148 George Street
ValueCountFrequency (%)
street 291
 
8.6%
avenue 233
 
6.9%
ave 96
 
2.8%
road 81
 
2.4%
east 57
 
1.7%
st 57
 
1.7%
west 50
 
1.5%
drive 33
 
1.0%
blvd 32
 
0.9%
rd 28
 
0.8%
Other values (1504) 2431
71.7%
2023-12-09T23:12:31.183595image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2397
 
13.3%
e 1766
 
9.8%
t 1297
 
7.2%
r 774
 
4.3%
1 738
 
4.1%
a 671
 
3.7%
n 657
 
3.6%
2 526
 
2.9%
o 517
 
2.9%
0 503
 
2.8%
Other values (58) 8244
45.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9139
50.5%
Decimal Number 3967
21.9%
Space Separator 2397
 
13.3%
Uppercase Letter 2313
 
12.8%
Dash Punctuation 144
 
0.8%
Other Punctuation 130
 
0.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 461
19.9%
A 405
17.5%
R 167
 
7.2%
E 142
 
6.1%
W 134
 
5.8%
B 123
 
5.3%
P 104
 
4.5%
C 91
 
3.9%
L 77
 
3.3%
D 73
 
3.2%
Other values (16) 536
23.2%
Lowercase Letter
ValueCountFrequency (%)
e 1766
19.3%
t 1297
14.2%
r 774
8.5%
a 671
 
7.3%
n 657
 
7.2%
o 517
 
5.7%
v 426
 
4.7%
d 401
 
4.4%
i 391
 
4.3%
u 378
 
4.1%
Other values (15) 1861
20.4%
Decimal Number
ValueCountFrequency (%)
1 738
18.6%
2 526
13.3%
0 503
12.7%
3 445
11.2%
5 387
9.8%
4 347
8.7%
6 305
7.7%
9 247
 
6.2%
8 236
 
5.9%
7 233
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 59
45.4%
, 47
36.2%
# 21
 
16.2%
' 2
 
1.5%
/ 1
 
0.8%
Space Separator
ValueCountFrequency (%)
2397
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 144
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11452
63.3%
Common 6638
36.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1766
15.4%
t 1297
 
11.3%
r 774
 
6.8%
a 671
 
5.9%
n 657
 
5.7%
o 517
 
4.5%
S 461
 
4.0%
v 426
 
3.7%
A 405
 
3.5%
d 401
 
3.5%
Other values (41) 4077
35.6%
Common
ValueCountFrequency (%)
2397
36.1%
1 738
 
11.1%
2 526
 
7.9%
0 503
 
7.6%
3 445
 
6.7%
5 387
 
5.8%
4 347
 
5.2%
6 305
 
4.6%
9 247
 
3.7%
8 236
 
3.6%
Other values (7) 507
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18090
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2397
 
13.3%
e 1766
 
9.8%
t 1297
 
7.2%
r 774
 
4.3%
1 738
 
4.1%
a 671
 
3.7%
n 657
 
3.6%
2 526
 
2.9%
o 517
 
2.9%
0 503
 
2.8%
Other values (58) 8244
45.6%

address2
Text

MISSING 

Distinct310
Distinct (%)81.2%
Missing618
Missing (%)61.8%
Memory size43.7 KiB
2023-12-09T23:12:31.659864image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length34
Median length32
Mean length7.916230366
Min length1

Characters and Unicode

Total characters3024
Distinct characters62
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique268 ?
Unique (%)70.2%

Sample

1st row#23D
2nd rowApt 4C
3rd rowSuite 203
4th rowGround Floor
5th rowSuite 5
ValueCountFrequency (%)
suite 162
21.8%
floor 62
 
8.3%
apt 46
 
6.2%
unit 17
 
2.3%
1 17
 
2.3%
14
 
1.9%
2 13
 
1.7%
1st 12
 
1.6%
3rd 10
 
1.3%
3 9
 
1.2%
Other values (263) 382
51.3%
2023-12-09T23:12:32.283541image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
362
 
12.0%
t 283
 
9.4%
i 192
 
6.3%
e 192
 
6.3%
1 176
 
5.8%
S 172
 
5.7%
u 172
 
5.7%
o 150
 
5.0%
0 120
 
4.0%
2 108
 
3.6%
Other values (52) 1097
36.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1378
45.6%
Decimal Number 708
23.4%
Uppercase Letter 507
 
16.8%
Space Separator 362
 
12.0%
Other Punctuation 68
 
2.2%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 283
20.5%
i 192
13.9%
e 192
13.9%
u 172
12.5%
o 150
10.9%
r 98
 
7.1%
l 73
 
5.3%
p 44
 
3.2%
n 44
 
3.2%
h 31
 
2.2%
Other values (13) 99
 
7.2%
Uppercase Letter
ValueCountFrequency (%)
S 172
33.9%
F 86
17.0%
A 66
 
13.0%
B 21
 
4.1%
U 20
 
3.9%
C 19
 
3.7%
D 17
 
3.4%
L 13
 
2.6%
P 12
 
2.4%
N 11
 
2.2%
Other values (12) 70
13.8%
Decimal Number
ValueCountFrequency (%)
1 176
24.9%
0 120
16.9%
2 108
15.3%
3 78
11.0%
4 66
 
9.3%
6 50
 
7.1%
5 48
 
6.8%
7 27
 
3.8%
8 19
 
2.7%
9 16
 
2.3%
Other Punctuation
ValueCountFrequency (%)
# 45
66.2%
. 10
 
14.7%
, 9
 
13.2%
/ 3
 
4.4%
& 1
 
1.5%
Space Separator
ValueCountFrequency (%)
362
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1885
62.3%
Common 1139
37.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 283
15.0%
i 192
10.2%
e 192
10.2%
S 172
9.1%
u 172
9.1%
o 150
 
8.0%
r 98
 
5.2%
F 86
 
4.6%
l 73
 
3.9%
A 66
 
3.5%
Other values (35) 401
21.3%
Common
ValueCountFrequency (%)
362
31.8%
1 176
15.5%
0 120
 
10.5%
2 108
 
9.5%
3 78
 
6.8%
4 66
 
5.8%
6 50
 
4.4%
5 48
 
4.2%
# 45
 
4.0%
7 27
 
2.4%
Other values (7) 59
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3024
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
362
 
12.0%
t 283
 
9.4%
i 192
 
6.3%
e 192
 
6.3%
1 176
 
5.8%
S 172
 
5.7%
u 172
 
5.7%
o 150
 
5.0%
0 120
 
4.0%
2 108
 
3.6%
Other values (52) 1097
36.3%

city
Text

Distinct307
Distinct (%)30.7%
Missing0
Missing (%)0.0%
Memory size64.7 KiB
2023-12-09T23:12:32.680609image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length19
Median length18
Mean length9.121
Min length4

Characters and Unicode

Total characters9121
Distinct characters52
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique197 ?
Unique (%)19.7%

Sample

1st rowBrooklyn
2nd rowRed Bank
3rd rowBronx
4th rowBrooklyn
5th rowBrooklyn
ValueCountFrequency (%)
new 188
 
12.9%
brooklyn 183
 
12.6%
york 173
 
11.9%
bronx 66
 
4.5%
island 51
 
3.5%
city 31
 
2.1%
staten 29
 
2.0%
park 27
 
1.9%
jamaica 22
 
1.5%
long 21
 
1.4%
Other values (303) 665
45.7%
2023-12-09T23:12:33.220417image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 899
 
9.9%
r 687
 
7.5%
n 687
 
7.5%
e 687
 
7.5%
l 540
 
5.9%
a 505
 
5.5%
k 458
 
5.0%
456
 
5.0%
i 338
 
3.7%
t 322
 
3.5%
Other values (42) 3542
38.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6909
75.7%
Uppercase Letter 1748
 
19.2%
Space Separator 456
 
5.0%
Other Punctuation 8
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 899
13.0%
r 687
9.9%
n 687
9.9%
e 687
9.9%
l 540
 
7.8%
a 505
 
7.3%
k 458
 
6.6%
i 338
 
4.9%
t 322
 
4.7%
s 314
 
4.5%
Other values (15) 1472
21.3%
Uppercase Letter
ValueCountFrequency (%)
B 294
16.8%
N 226
12.9%
Y 196
 
11.2%
S 107
 
6.1%
R 81
 
4.6%
H 73
 
4.2%
I 68
 
3.9%
M 66
 
3.8%
L 65
 
3.7%
C 65
 
3.7%
Other values (15) 507
29.0%
Space Separator
ValueCountFrequency (%)
456
100.0%
Other Punctuation
ValueCountFrequency (%)
. 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8657
94.9%
Common 464
 
5.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 899
 
10.4%
r 687
 
7.9%
n 687
 
7.9%
e 687
 
7.9%
l 540
 
6.2%
a 505
 
5.8%
k 458
 
5.3%
i 338
 
3.9%
t 322
 
3.7%
s 314
 
3.6%
Other values (40) 3220
37.2%
Common
ValueCountFrequency (%)
456
98.3%
. 8
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9121
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 899
 
9.9%
r 687
 
7.5%
n 687
 
7.5%
e 687
 
7.5%
l 540
 
5.9%
a 505
 
5.5%
k 458
 
5.0%
456
 
5.0%
i 338
 
3.7%
t 322
 
3.5%
Other values (42) 3542
38.8%

state
Text

Distinct21
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2023-12-09T23:12:33.382844image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2000
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)1.0%

Sample

1st rowNY
2nd rowNJ
3rd rowNY
4th rowNY
5th rowNY
ValueCountFrequency (%)
ny 872
87.2%
nj 91
 
9.1%
pa 7
 
0.7%
ga 4
 
0.4%
ct 3
 
0.3%
il 3
 
0.3%
va 2
 
0.2%
ca 2
 
0.2%
md 2
 
0.2%
ma 2
 
0.2%
Other values (11) 12
 
1.2%
2023-12-09T23:12:33.638793image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 966
48.3%
Y 872
43.6%
J 91
 
4.5%
A 17
 
0.9%
C 9
 
0.4%
P 7
 
0.4%
M 6
 
0.3%
I 6
 
0.3%
D 4
 
0.2%
L 4
 
0.2%
Other values (9) 18
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2000
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 966
48.3%
Y 872
43.6%
J 91
 
4.5%
A 17
 
0.9%
C 9
 
0.4%
P 7
 
0.4%
M 6
 
0.3%
I 6
 
0.3%
D 4
 
0.2%
L 4
 
0.2%
Other values (9) 18
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 2000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 966
48.3%
Y 872
43.6%
J 91
 
4.5%
A 17
 
0.9%
C 9
 
0.4%
P 7
 
0.4%
M 6
 
0.3%
I 6
 
0.3%
D 4
 
0.2%
L 4
 
0.2%
Other values (9) 18
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 966
48.3%
Y 872
43.6%
J 91
 
4.5%
A 17
 
0.9%
C 9
 
0.4%
P 7
 
0.4%
M 6
 
0.3%
I 6
 
0.3%
D 4
 
0.2%
L 4
 
0.2%
Other values (9) 18
 
0.9%

zip
Text

Distinct410
Distinct (%)41.0%
Missing0
Missing (%)0.0%
Memory size60.6 KiB
2023-12-09T23:12:34.029756image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.902
Min length4

Characters and Unicode

Total characters4902
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique206 ?
Unique (%)20.6%

Sample

1st row11211
2nd row7701
3rd row10475
4th row11238
5th row11237
ValueCountFrequency (%)
10001 19
 
1.9%
11101 17
 
1.7%
11201 13
 
1.3%
10018 11
 
1.1%
11230 11
 
1.1%
11238 10
 
1.0%
11432 9
 
0.9%
11801 9
 
0.9%
11226 9
 
0.9%
11413 8
 
0.8%
Other values (400) 884
88.4%
2023-12-09T23:12:34.544416image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1788
36.5%
0 904
18.4%
2 450
 
9.2%
3 351
 
7.2%
7 320
 
6.5%
4 288
 
5.9%
5 284
 
5.8%
6 224
 
4.6%
8 169
 
3.4%
9 124
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4902
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1788
36.5%
0 904
18.4%
2 450
 
9.2%
3 351
 
7.2%
7 320
 
6.5%
4 288
 
5.9%
5 284
 
5.8%
6 224
 
4.6%
8 169
 
3.4%
9 124
 
2.5%

Most occurring scripts

ValueCountFrequency (%)
Common 4902
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1788
36.5%
0 904
18.4%
2 450
 
9.2%
3 351
 
7.2%
7 320
 
6.5%
4 288
 
5.9%
5 284
 
5.8%
6 224
 
4.6%
8 169
 
3.4%
9 124
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4902
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1788
36.5%
0 904
18.4%
2 450
 
9.2%
3 351
 
7.2%
7 320
 
6.5%
4 288
 
5.9%
5 284
 
5.8%
6 224
 
4.6%
8 169
 
3.4%
9 124
 
2.5%
Distinct991
Distinct (%)99.2%
Missing1
Missing (%)0.1%
Memory size73.3 KiB
2023-12-09T23:12:36.929340image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length37
Median length31
Mean length17.92492492
Min length8

Characters and Unicode

Total characters17907
Distinct characters66
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique983 ?
Unique (%)98.4%

Sample

1st row208 Grand Street
2nd row9 Globe Ct
3rd row120 Elgar Place
4th row946 Atlantic Ave
5th row148 George Street
ValueCountFrequency (%)
street 281
 
8.3%
avenue 232
 
6.9%
ave 88
 
2.6%
road 81
 
2.4%
east 61
 
1.8%
st 55
 
1.6%
west 50
 
1.5%
drive 37
 
1.1%
box 32
 
0.9%
blvd 31
 
0.9%
Other values (1506) 2428
71.9%
2023-12-09T23:12:37.547932image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2382
 
13.3%
e 1718
 
9.6%
t 1243
 
6.9%
r 759
 
4.2%
1 740
 
4.1%
a 654
 
3.7%
n 645
 
3.6%
o 526
 
2.9%
2 512
 
2.9%
0 509
 
2.8%
Other values (56) 8219
45.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8953
50.0%
Decimal Number 3971
22.2%
Space Separator 2382
 
13.3%
Uppercase Letter 2333
 
13.0%
Dash Punctuation 137
 
0.8%
Other Punctuation 131
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1718
19.2%
t 1243
13.9%
r 759
8.5%
a 654
 
7.3%
n 645
 
7.2%
o 526
 
5.9%
v 423
 
4.7%
d 389
 
4.3%
i 388
 
4.3%
u 365
 
4.1%
Other values (15) 1843
20.6%
Uppercase Letter
ValueCountFrequency (%)
S 441
18.9%
A 394
16.9%
R 167
 
7.2%
B 142
 
6.1%
E 138
 
5.9%
P 133
 
5.7%
W 128
 
5.5%
C 80
 
3.4%
D 79
 
3.4%
L 77
 
3.3%
Other values (15) 554
23.7%
Decimal Number
ValueCountFrequency (%)
1 740
18.6%
2 512
12.9%
0 509
12.8%
3 436
11.0%
5 389
9.8%
4 350
8.8%
6 326
8.2%
9 245
 
6.2%
7 238
 
6.0%
8 226
 
5.7%
Other Punctuation
ValueCountFrequency (%)
. 70
53.4%
, 39
29.8%
# 20
 
15.3%
' 2
 
1.5%
Space Separator
ValueCountFrequency (%)
2382
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 137
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11286
63.0%
Common 6621
37.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1718
15.2%
t 1243
 
11.0%
r 759
 
6.7%
a 654
 
5.8%
n 645
 
5.7%
o 526
 
4.7%
S 441
 
3.9%
v 423
 
3.7%
A 394
 
3.5%
d 389
 
3.4%
Other values (40) 4094
36.3%
Common
ValueCountFrequency (%)
2382
36.0%
1 740
 
11.2%
2 512
 
7.7%
0 509
 
7.7%
3 436
 
6.6%
5 389
 
5.9%
4 350
 
5.3%
6 326
 
4.9%
9 245
 
3.7%
7 238
 
3.6%
Other values (6) 494
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17907
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2382
 
13.3%
e 1718
 
9.6%
t 1243
 
6.9%
r 759
 
4.2%
1 740
 
4.1%
a 654
 
3.7%
n 645
 
3.6%
o 526
 
2.9%
2 512
 
2.9%
0 509
 
2.8%
Other values (56) 8219
45.9%

mailingaddress2
Text

MISSING 

Distinct330
Distinct (%)84.0%
Missing607
Missing (%)60.7%
Memory size44.0 KiB
2023-12-09T23:12:38.023269image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length34
Median length25
Mean length7.786259542
Min length1

Characters and Unicode

Total characters3060
Distinct characters62
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique294 ?
Unique (%)74.8%

Sample

1st row#23D
2nd rowApt 4C
3rd row#16F
4th rowGround Floor
5th rowApt 8G
ValueCountFrequency (%)
suite 160
 
21.1%
floor 57
 
7.5%
apt 54
 
7.1%
unit 16
 
2.1%
1 16
 
2.1%
1st 13
 
1.7%
12
 
1.6%
2 11
 
1.4%
3rd 9
 
1.2%
2nd 9
 
1.2%
Other values (285) 402
53.0%
2023-12-09T23:12:38.643786image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
366
 
12.0%
t 284
 
9.3%
e 189
 
6.2%
i 187
 
6.1%
1 186
 
6.1%
S 172
 
5.6%
u 169
 
5.5%
o 140
 
4.6%
0 124
 
4.1%
2 112
 
3.7%
Other values (52) 1131
37.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1343
43.9%
Decimal Number 759
24.8%
Uppercase Letter 522
 
17.1%
Space Separator 366
 
12.0%
Other Punctuation 69
 
2.3%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 172
33.0%
F 81
15.5%
A 74
14.2%
B 24
 
4.6%
U 20
 
3.8%
L 17
 
3.3%
C 15
 
2.9%
D 14
 
2.7%
P 14
 
2.7%
T 12
 
2.3%
Other values (13) 79
15.1%
Lowercase Letter
ValueCountFrequency (%)
t 284
21.1%
e 189
14.1%
i 187
13.9%
u 169
12.6%
o 140
10.4%
r 86
 
6.4%
l 68
 
5.1%
p 52
 
3.9%
n 42
 
3.1%
h 29
 
2.2%
Other values (12) 97
 
7.2%
Decimal Number
ValueCountFrequency (%)
1 186
24.5%
0 124
16.3%
2 112
14.8%
3 85
11.2%
4 70
 
9.2%
6 51
 
6.7%
5 51
 
6.7%
7 35
 
4.6%
8 25
 
3.3%
9 20
 
2.6%
Other Punctuation
ValueCountFrequency (%)
# 46
66.7%
. 11
 
15.9%
, 8
 
11.6%
/ 3
 
4.3%
& 1
 
1.4%
Space Separator
ValueCountFrequency (%)
366
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1865
60.9%
Common 1195
39.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 284
15.2%
e 189
10.1%
i 187
10.0%
S 172
9.2%
u 169
9.1%
o 140
 
7.5%
r 86
 
4.6%
F 81
 
4.3%
A 74
 
4.0%
l 68
 
3.6%
Other values (35) 415
22.3%
Common
ValueCountFrequency (%)
366
30.6%
1 186
15.6%
0 124
 
10.4%
2 112
 
9.4%
3 85
 
7.1%
4 70
 
5.9%
6 51
 
4.3%
5 51
 
4.3%
# 46
 
3.8%
7 35
 
2.9%
Other values (7) 69
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3060
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
366
 
12.0%
t 284
 
9.3%
e 189
 
6.2%
i 187
 
6.1%
1 186
 
6.1%
S 172
 
5.6%
u 169
 
5.5%
o 140
 
4.6%
0 124
 
4.1%
2 112
 
3.7%
Other values (52) 1131
37.0%
Distinct311
Distinct (%)31.1%
Missing1
Missing (%)0.1%
Memory size64.7 KiB
2023-12-09T23:12:38.979132image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length19
Median length18
Mean length9.138138138
Min length4

Characters and Unicode

Total characters9129
Distinct characters52
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique195 ?
Unique (%)19.5%

Sample

1st rowBrooklyn
2nd rowRed Bank
3rd rowBronx
4th rowBrooklyn
5th rowBrooklyn
ValueCountFrequency (%)
new 186
 
12.7%
york 172
 
11.8%
brooklyn 170
 
11.6%
bronx 65
 
4.5%
island 52
 
3.6%
city 31
 
2.1%
staten 30
 
2.1%
park 26
 
1.8%
jamaica 21
 
1.4%
long 20
 
1.4%
Other values (300) 687
47.1%
2023-12-09T23:12:39.450726image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 897
 
9.8%
n 682
 
7.5%
r 680
 
7.4%
e 674
 
7.4%
l 533
 
5.8%
a 517
 
5.7%
461
 
5.0%
k 455
 
5.0%
i 338
 
3.7%
t 330
 
3.6%
Other values (42) 3562
39.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6918
75.8%
Uppercase Letter 1741
 
19.1%
Space Separator 461
 
5.0%
Other Punctuation 9
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 897
13.0%
n 682
9.9%
r 680
9.8%
e 674
9.7%
l 533
 
7.7%
a 517
 
7.5%
k 455
 
6.6%
i 338
 
4.9%
t 330
 
4.8%
s 315
 
4.6%
Other values (15) 1497
21.6%
Uppercase Letter
ValueCountFrequency (%)
B 288
16.5%
N 224
12.9%
Y 191
 
11.0%
S 120
 
6.9%
R 77
 
4.4%
H 75
 
4.3%
M 69
 
4.0%
I 67
 
3.8%
C 66
 
3.8%
L 64
 
3.7%
Other values (15) 500
28.7%
Space Separator
ValueCountFrequency (%)
461
100.0%
Other Punctuation
ValueCountFrequency (%)
. 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8659
94.9%
Common 470
 
5.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 897
 
10.4%
n 682
 
7.9%
r 680
 
7.9%
e 674
 
7.8%
l 533
 
6.2%
a 517
 
6.0%
k 455
 
5.3%
i 338
 
3.9%
t 330
 
3.8%
s 315
 
3.6%
Other values (40) 3238
37.4%
Common
ValueCountFrequency (%)
461
98.1%
. 9
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9129
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 897
 
9.8%
n 682
 
7.5%
r 680
 
7.4%
e 674
 
7.4%
l 533
 
5.8%
a 517
 
5.7%
461
 
5.0%
k 455
 
5.0%
i 338
 
3.7%
t 330
 
3.6%
Other values (42) 3562
39.0%
Distinct21
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size63.8 KiB
2023-12-09T23:12:39.663895image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length20
Median length8
Mean length8.253
Min length4

Characters and Unicode

Total characters8253
Distinct characters38
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)1.0%

Sample

1st rowNew York
2nd rowNew Jersey
3rd rowNew York
4th rowNew York
5th rowNew York
ValueCountFrequency (%)
new 963
48.9%
york 872
44.3%
jersey 91
 
4.6%
pennsylvania 7
 
0.4%
georgia 4
 
0.2%
connecticut 3
 
0.2%
illinois 3
 
0.2%
maryland 2
 
0.1%
california 2
 
0.1%
massachusetts 2
 
0.1%
Other values (16) 20
 
1.0%
2023-12-09T23:12:40.022180image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1165
14.1%
r 978
11.9%
969
11.7%
N 964
11.7%
w 963
11.7%
o 897
10.9%
Y 872
10.6%
k 872
10.6%
s 114
 
1.4%
y 100
 
1.2%
Other values (28) 359
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5317
64.4%
Uppercase Letter 1967
 
23.8%
Space Separator 969
 
11.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1165
21.9%
r 978
18.4%
w 963
18.1%
o 897
16.9%
k 872
16.4%
s 114
 
2.1%
y 100
 
1.9%
a 46
 
0.9%
n 43
 
0.8%
i 43
 
0.8%
Other values (12) 96
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
N 964
49.0%
Y 872
44.3%
J 91
 
4.6%
C 9
 
0.5%
P 7
 
0.4%
M 6
 
0.3%
I 5
 
0.3%
G 4
 
0.2%
D 2
 
0.1%
V 2
 
0.1%
Other values (5) 5
 
0.3%
Space Separator
ValueCountFrequency (%)
969
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7284
88.3%
Common 969
 
11.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1165
16.0%
r 978
13.4%
N 964
13.2%
w 963
13.2%
o 897
12.3%
Y 872
12.0%
k 872
12.0%
s 114
 
1.6%
y 100
 
1.4%
J 91
 
1.2%
Other values (27) 268
 
3.7%
Common
ValueCountFrequency (%)
969
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8253
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1165
14.1%
r 978
11.9%
969
11.7%
N 964
11.7%
w 963
11.7%
o 897
10.9%
Y 872
10.6%
k 872
10.6%
s 114
 
1.4%
y 100
 
1.2%
Other values (28) 359
 
4.3%
Distinct422
Distinct (%)42.2%
Missing1
Missing (%)0.1%
Memory size60.5 KiB
2023-12-09T23:12:40.437706image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.897897898
Min length4

Characters and Unicode

Total characters4893
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique220 ?
Unique (%)22.0%

Sample

1st row11211
2nd row7701
3rd row10475
4th row11238
5th row11237
ValueCountFrequency (%)
10001 20
 
2.0%
11101 17
 
1.7%
11201 14
 
1.4%
11238 12
 
1.2%
11230 11
 
1.1%
10013 10
 
1.0%
11205 9
 
0.9%
11801 9
 
0.9%
10018 9
 
0.9%
11432 8
 
0.8%
Other values (412) 880
88.1%
2023-12-09T23:12:40.974875image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1765
36.1%
0 918
18.8%
2 443
 
9.1%
3 366
 
7.5%
7 321
 
6.6%
4 281
 
5.7%
5 267
 
5.5%
6 224
 
4.6%
8 179
 
3.7%
9 129
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4893
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1765
36.1%
0 918
18.8%
2 443
 
9.1%
3 366
 
7.5%
7 321
 
6.6%
4 281
 
5.7%
5 267
 
5.5%
6 224
 
4.6%
8 179
 
3.7%
9 129
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
Common 4893
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1765
36.1%
0 918
18.8%
2 443
 
9.1%
3 366
 
7.5%
7 321
 
6.6%
4 281
 
5.7%
5 267
 
5.5%
6 224
 
4.6%
8 179
 
3.7%
9 129
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4893
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1765
36.1%
0 918
18.8%
2 443
 
9.1%
3 366
 
7.5%
7 321
 
6.6%
4 281
 
5.7%
5 267
 
5.5%
6 224
 
4.6%
8 179
 
3.7%
9 129
 
2.6%

website
URL

MISSING 

Distinct714
Distinct (%)99.6%
Missing283
Missing (%)28.3%
Memory size68.3 KiB
http://www.3gwhse.com
 
2
http://www.activeworldnyc.com
 
2
http://www.alwaysfirstdemo.com
 
2
http://www.afiglass.com
 
1
http://www.amarachirestaurant.com
 
1
Other values (709)
709 
(Missing)
283 
ValueCountFrequency (%)
http://www.3gwhse.com 2
 
0.2%
http://www.activeworldnyc.com 2
 
0.2%
http://www.alwaysfirstdemo.com 2
 
0.2%
http://www.afiglass.com 1
 
0.1%
http://www.amarachirestaurant.com 1
 
0.1%
http://ammep.com 1
 
0.1%
http://www.asrnyc.com 1
 
0.1%
http://www.allpointscom.com 1
 
0.1%
https://arc-geo.com 1
 
0.1%
https://resolutionmanagement.com 1
 
0.1%
Other values (704) 704
70.4%
(Missing) 283
28.3%
ValueCountFrequency (%)
http 608
60.8%
https 109
 
10.9%
(Missing) 283
28.3%
ValueCountFrequency (%)
www.3gwhse.com 2
 
0.2%
www.activeworldnyc.com 2
 
0.2%
www.alwaysfirstdemo.com 2
 
0.2%
4futuregenerations.com 1
 
0.1%
www.ArgentoUSA.com 1
 
0.1%
www.alantesecurity.com 1
 
0.1%
1starnetworks.com 1
 
0.1%
American Awning & Sign Depot, Inc. 1
 
0.1%
www.aof-isi.com 1
 
0.1%
www.blsecuritygroup.com 1
 
0.1%
Other values (704) 704
70.4%
(Missing) 283
28.3%
ValueCountFrequency (%)
675
67.5%
/ 33
 
3.3%
/jerseycity 1
 
0.1%
/ * https://helloinsight.org/ 1
 
0.1%
/new-york/staten-island/comfort-inn-hotels/ny470 1
 
0.1%
//www.nyallran.com 1
 
0.1%
/ride-with-us/ 1
 
0.1%
/hotels/travel/nycal-aloft-manhattan-downtown-financial-district/ 1
 
0.1%
/newworldbiz1 1
 
0.1%
/new-york 1
 
0.1%
(Missing) 283
28.3%
ValueCountFrequency (%)
717
71.7%
(Missing) 283
 
28.3%
ValueCountFrequency (%)
717
71.7%
(Missing) 283
 
28.3%

date_of_establishment
Text

MISSING 

Distinct847
Distinct (%)92.5%
Missing84
Missing (%)8.4%
Memory size74.3 KiB
2023-12-09T23:12:41.252561image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters21068
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique787 ?
Unique (%)85.9%

Sample

1st row2019-06-15T00:00:00.000
2nd row2014-12-16T00:00:00.000
3rd row2019-02-08T00:00:00.000
4th row2004-02-02T00:00:00.000
5th row2018-08-23T00:00:00.000
ValueCountFrequency (%)
2018-01-01t00:00:00.000 4
 
0.4%
2005-01-01t00:00:00.000 4
 
0.4%
2017-02-13t00:00:00.000 3
 
0.3%
2000-01-01t00:00:00.000 3
 
0.3%
2016-01-15t00:00:00.000 3
 
0.3%
2017-01-09t00:00:00.000 3
 
0.3%
2006-01-01t00:00:00.000 3
 
0.3%
2006-04-26t00:00:00.000 2
 
0.2%
2015-06-12t00:00:00.000 2
 
0.2%
2011-01-01t00:00:00.000 2
 
0.2%
Other values (837) 887
96.8%
2023-12-09T23:12:41.652946image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10601
50.3%
- 1832
 
8.7%
: 1832
 
8.7%
1 1526
 
7.2%
2 1361
 
6.5%
T 916
 
4.3%
. 916
 
4.3%
9 506
 
2.4%
3 287
 
1.4%
8 278
 
1.3%
Other values (4) 1013
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15572
73.9%
Other Punctuation 2748
 
13.0%
Dash Punctuation 1832
 
8.7%
Uppercase Letter 916
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10601
68.1%
1 1526
 
9.8%
2 1361
 
8.7%
9 506
 
3.2%
3 287
 
1.8%
8 278
 
1.8%
6 264
 
1.7%
4 261
 
1.7%
5 249
 
1.6%
7 239
 
1.5%
Other Punctuation
ValueCountFrequency (%)
: 1832
66.7%
. 916
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1832
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 916
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20152
95.7%
Latin 916
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10601
52.6%
- 1832
 
9.1%
: 1832
 
9.1%
1 1526
 
7.6%
2 1361
 
6.8%
. 916
 
4.5%
9 506
 
2.5%
3 287
 
1.4%
8 278
 
1.4%
6 264
 
1.3%
Other values (3) 749
 
3.7%
Latin
ValueCountFrequency (%)
T 916
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21068
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10601
50.3%
- 1832
 
8.7%
: 1832
 
8.7%
1 1526
 
7.2%
2 1361
 
6.5%
T 916
 
4.3%
. 916
 
4.3%
9 506
 
2.4%
3 287
 
1.4%
8 278
 
1.3%
Other values (4) 1013
 
4.8%
Distinct39
Distinct (%)35.5%
Missing890
Missing (%)89.0%
Memory size34.8 KiB
2023-12-09T23:12:41.921731image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length9
Mean length6.863636364
Min length3

Characters and Unicode

Total characters755
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)18.2%

Sample

1st row10000000
2nd row1000000
3rd row7000000
4th row100000
5th row750000
ValueCountFrequency (%)
50000 11
 
10.0%
1000000 10
 
9.1%
10000 9
 
8.2%
10000000 9
 
8.2%
3000000 7
 
6.4%
2000000 7
 
6.4%
25000000 5
 
4.5%
20000000 4
 
3.6%
4000000 4
 
3.6%
50000000 3
 
2.7%
Other values (29) 41
37.3%
2023-12-09T23:12:42.316248image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 609
80.7%
1 44
 
5.8%
5 41
 
5.4%
2 23
 
3.0%
4 14
 
1.9%
3 10
 
1.3%
7 5
 
0.7%
8 4
 
0.5%
9 3
 
0.4%
6 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 754
99.9%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 609
80.8%
1 44
 
5.8%
5 41
 
5.4%
2 23
 
3.1%
4 14
 
1.9%
3 10
 
1.3%
7 5
 
0.7%
8 4
 
0.5%
9 3
 
0.4%
6 1
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 755
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 609
80.7%
1 44
 
5.8%
5 41
 
5.4%
2 23
 
3.0%
4 14
 
1.9%
3 10
 
1.3%
7 5
 
0.7%
8 4
 
0.5%
9 3
 
0.4%
6 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 755
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 609
80.7%
1 44
 
5.8%
5 41
 
5.4%
2 23
 
3.0%
4 14
 
1.9%
3 10
 
1.3%
7 5
 
0.7%
8 4
 
0.5%
9 3
 
0.4%
6 1
 
0.1%
Distinct68
Distinct (%)98.6%
Missing931
Missing (%)93.1%
Memory size36.2 KiB
2023-12-09T23:12:42.647392image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length100
Median length70
Mean length46.14492754
Min length6

Characters and Unicode

Total characters3184
Distinct characters64
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)97.1%

Sample

1st rowI.U.O.E Operating Engineers 15, Building, Concrete Excavating & Common Laborer's Union 731
2nd rowUnion Local 78 78, Union Local 12A 12A
3rd rowMason Tender 79, Laborer Union 20
4th rowDistrict Council 9 NY 1087, NY District Council of Carpenters 157
5th rowPavers & Road Builders 1010, Construction & General Building Laborers 79, General Building Laborers
ValueCountFrequency (%)
local 27
 
5.3%
union 22
 
4.3%
laborers 17
 
3.3%
of 15
 
2.9%
3 13
 
2.5%
79 13
 
2.5%
ibew 11
 
2.1%
metal 10
 
2.0%
mason 10
 
2.0%
78 9
 
1.8%
Other values (171) 365
71.3%
2023-12-09T23:12:43.131532image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
454
 
14.3%
e 221
 
6.9%
r 220
 
6.9%
n 180
 
5.7%
o 178
 
5.6%
a 164
 
5.2%
s 137
 
4.3%
t 136
 
4.3%
i 136
 
4.3%
l 96
 
3.0%
Other values (54) 1262
39.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1823
57.3%
Uppercase Letter 466
 
14.6%
Space Separator 454
 
14.3%
Decimal Number 336
 
10.6%
Other Punctuation 99
 
3.1%
Dash Punctuation 4
 
0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 221
12.1%
r 220
12.1%
n 180
9.9%
o 178
9.8%
a 164
9.0%
s 137
7.5%
t 136
7.5%
i 136
7.5%
l 96
 
5.3%
c 74
 
4.1%
Other values (13) 281
15.4%
Uppercase Letter
ValueCountFrequency (%)
L 53
11.4%
C 44
 
9.4%
I 38
 
8.2%
E 38
 
8.2%
A 34
 
7.3%
U 30
 
6.4%
T 29
 
6.2%
B 29
 
6.2%
M 22
 
4.7%
S 21
 
4.5%
Other values (11) 128
27.5%
Decimal Number
ValueCountFrequency (%)
1 58
17.3%
8 42
12.5%
2 39
11.6%
7 39
11.6%
3 33
9.8%
0 30
8.9%
5 25
7.4%
6 25
7.4%
4 23
 
6.8%
9 22
 
6.5%
Other Punctuation
ValueCountFrequency (%)
, 76
76.8%
. 9
 
9.1%
' 5
 
5.1%
& 5
 
5.1%
/ 3
 
3.0%
# 1
 
1.0%
Space Separator
ValueCountFrequency (%)
454
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2289
71.9%
Common 895
 
28.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 221
 
9.7%
r 220
 
9.6%
n 180
 
7.9%
o 178
 
7.8%
a 164
 
7.2%
s 137
 
6.0%
t 136
 
5.9%
i 136
 
5.9%
l 96
 
4.2%
c 74
 
3.2%
Other values (34) 747
32.6%
Common
ValueCountFrequency (%)
454
50.7%
, 76
 
8.5%
1 58
 
6.5%
8 42
 
4.7%
2 39
 
4.4%
7 39
 
4.4%
3 33
 
3.7%
0 30
 
3.4%
5 25
 
2.8%
6 25
 
2.8%
Other values (10) 74
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3184
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
454
 
14.3%
e 221
 
6.9%
r 220
 
6.9%
n 180
 
5.7%
o 178
 
5.6%
a 164
 
5.2%
s 137
 
4.3%
t 136
 
4.3%
i 136
 
4.3%
l 96
 
3.0%
Other values (54) 1262
39.6%
Distinct247
Distinct (%)24.7%
Missing0
Missing (%)0.0%
Memory size61.6 KiB
2023-12-09T23:12:43.472720image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6000
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique113 ?
Unique (%)11.3%

Sample

1st row722511
2nd row541330
3rd row453998
4th row561720
5th row621610
ValueCountFrequency (%)
541330 40
 
4.0%
541310 39
 
3.9%
236220 31
 
3.1%
541990 30
 
3.0%
238990 29
 
2.9%
236118 28
 
2.8%
238210 27
 
2.7%
541611 27
 
2.7%
561720 24
 
2.4%
611710 21
 
2.1%
Other values (237) 704
70.4%
2023-12-09T23:12:43.929754image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1358
22.6%
2 808
13.5%
0 750
12.5%
3 715
11.9%
5 588
9.8%
4 570
9.5%
9 410
 
6.8%
6 368
 
6.1%
8 305
 
5.1%
7 128
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1358
22.6%
2 808
13.5%
0 750
12.5%
3 715
11.9%
5 588
9.8%
4 570
9.5%
9 410
 
6.8%
6 368
 
6.1%
8 305
 
5.1%
7 128
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
Common 6000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1358
22.6%
2 808
13.5%
0 750
12.5%
3 715
11.9%
5 588
9.8%
4 570
9.5%
9 410
 
6.8%
6 368
 
6.1%
8 305
 
5.1%
7 128
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1358
22.6%
2 808
13.5%
0 750
12.5%
3 715
11.9%
5 588
9.8%
4 570
9.5%
9 410
 
6.8%
6 368
 
6.1%
8 305
 
5.1%
7 128
 
2.1%
Distinct19
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size87.1 KiB
2023-12-09T23:12:44.196302image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length72
Median length48
Mean length32.012
Min length9

Characters and Unicode

Total characters32012
Distinct characters40
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowAccommodation and Food Services
2nd rowProfessional, Scientific, and Technical Services
3rd rowRetail Trade
4th rowAdministrative and Support and Waste Management and Remediation Services
5th rowHealth Care and Social Assistance
ValueCountFrequency (%)
and 722
20.3%
services 473
13.3%
professional 295
 
8.3%
scientific 295
 
8.3%
technical 295
 
8.3%
construction 257
 
7.2%
management 89
 
2.5%
administrative 88
 
2.5%
support 88
 
2.5%
waste 88
 
2.5%
Other values (36) 871
24.5%
2023-12-09T23:12:44.590332image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 3152
 
9.8%
n 3054
 
9.5%
e 2944
 
9.2%
2561
 
8.0%
a 2516
 
7.9%
c 2220
 
6.9%
t 1919
 
6.0%
s 1801
 
5.6%
o 1709
 
5.3%
r 1611
 
5.0%
Other values (30) 8525
26.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 25948
81.1%
Uppercase Letter 2815
 
8.8%
Space Separator 2561
 
8.0%
Other Punctuation 642
 
2.0%
Open Punctuation 23
 
0.1%
Close Punctuation 23
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 3152
12.1%
n 3054
11.8%
e 2944
11.3%
a 2516
9.7%
c 2220
8.6%
t 1919
7.4%
s 1801
6.9%
o 1709
6.6%
r 1611
6.2%
d 1092
 
4.2%
Other values (11) 3930
15.1%
Uppercase Letter
ValueCountFrequency (%)
S 889
31.6%
T 397
14.1%
P 324
 
11.5%
C 291
 
10.3%
A 201
 
7.1%
R 182
 
6.5%
W 154
 
5.5%
M 133
 
4.7%
E 84
 
3.0%
F 44
 
1.6%
Other values (5) 116
 
4.1%
Space Separator
ValueCountFrequency (%)
2561
100.0%
Other Punctuation
ValueCountFrequency (%)
, 642
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 28763
89.9%
Common 3249
 
10.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 3152
11.0%
n 3054
10.6%
e 2944
10.2%
a 2516
 
8.7%
c 2220
 
7.7%
t 1919
 
6.7%
s 1801
 
6.3%
o 1709
 
5.9%
r 1611
 
5.6%
d 1092
 
3.8%
Other values (26) 6745
23.5%
Common
ValueCountFrequency (%)
2561
78.8%
, 642
 
19.8%
( 23
 
0.7%
) 23
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32012
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 3152
 
9.8%
n 3054
 
9.5%
e 2944
 
9.2%
2561
 
8.0%
a 2516
 
7.9%
c 2220
 
6.9%
t 1919
 
6.0%
s 1801
 
5.6%
o 1709
 
5.3%
r 1611
 
5.0%
Other values (30) 8525
26.6%
Distinct145
Distinct (%)14.5%
Missing0
Missing (%)0.0%
Memory size95.9 KiB
2023-12-09T23:12:44.934986image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length102
Median length71
Mean length41.027
Min length12

Characters and Unicode

Total characters41027
Distinct characters52
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)5.5%

Sample

1st rowRestaurants and Other Eating Places
2nd rowArchitectural, Engineering, and Related Services
3rd rowOther Miscellaneous Store Retailers
4th rowServices to Buildings and Dwellings
5th rowHome Health Care Services
ValueCountFrequency (%)
and 611
 
13.0%
services 453
 
9.7%
building 215
 
4.6%
other 189
 
4.0%
contractors 175
 
3.7%
related 160
 
3.4%
technical 115
 
2.5%
scientific 114
 
2.4%
architectural 90
 
1.9%
engineering 89
 
1.9%
Other values (308) 2477
52.8%
2023-12-09T23:12:45.467065image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 4016
 
9.8%
3688
 
9.0%
i 3570
 
8.7%
n 3338
 
8.1%
t 2729
 
6.7%
r 2639
 
6.4%
a 2496
 
6.1%
s 2010
 
4.9%
c 1993
 
4.9%
o 1718
 
4.2%
Other values (42) 12830
31.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 32584
79.4%
Uppercase Letter 3998
 
9.7%
Space Separator 3688
 
9.0%
Other Punctuation 755
 
1.8%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4016
12.3%
i 3570
11.0%
n 3338
10.2%
t 2729
8.4%
r 2639
8.1%
a 2496
 
7.7%
s 2010
 
6.2%
c 1993
 
6.1%
o 1718
 
5.3%
l 1533
 
4.7%
Other values (15) 6542
20.1%
Uppercase Letter
ValueCountFrequency (%)
S 903
22.6%
C 430
10.8%
E 306
 
7.7%
B 303
 
7.6%
R 297
 
7.4%
A 245
 
6.1%
P 236
 
5.9%
O 218
 
5.5%
T 217
 
5.4%
M 215
 
5.4%
Other values (12) 628
15.7%
Other Punctuation
ValueCountFrequency (%)
, 753
99.7%
; 2
 
0.3%
Space Separator
ValueCountFrequency (%)
3688
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 36582
89.2%
Common 4445
 
10.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4016
 
11.0%
i 3570
 
9.8%
n 3338
 
9.1%
t 2729
 
7.5%
r 2639
 
7.2%
a 2496
 
6.8%
s 2010
 
5.5%
c 1993
 
5.4%
o 1718
 
4.7%
l 1533
 
4.2%
Other values (37) 10540
28.8%
Common
ValueCountFrequency (%)
3688
83.0%
, 753
 
16.9%
; 2
 
< 0.1%
( 1
 
< 0.1%
) 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41027
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 4016
 
9.8%
3688
 
9.0%
i 3570
 
8.7%
n 3338
 
8.1%
t 2729
 
6.7%
r 2639
 
6.4%
a 2496
 
6.1%
s 2010
 
4.9%
c 1993
 
4.9%
o 1718
 
4.2%
Other values (42) 12830
31.3%
Distinct247
Distinct (%)24.8%
Missing3
Missing (%)0.3%
Memory size92.6 KiB
2023-12-09T23:12:45.760680image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length107
Median length68
Mean length37.84653962
Min length8

Characters and Unicode

Total characters37733
Distinct characters53
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique113 ?
Unique (%)11.3%

Sample

1st rowFull-Service Restaurants
2nd rowEngineering Services
3rd rowAll Other Miscellaneous Store Retailers (except Tobacco Stores)
4th rowJanitorial Services
5th rowHome Health Care Services
ValueCountFrequency (%)
and 441
 
10.0%
services 406
 
9.2%
other 243
 
5.5%
contractors 204
 
4.6%
all 97
 
2.2%
management 71
 
1.6%
consulting 66
 
1.5%
building 60
 
1.4%
construction 55
 
1.3%
technical 47
 
1.1%
Other values (465) 2707
61.6%
2023-12-09T23:12:46.206979image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 3629
 
9.6%
3400
 
9.0%
i 2876
 
7.6%
r 2821
 
7.5%
n 2815
 
7.5%
t 2656
 
7.0%
a 2427
 
6.4%
s 2000
 
5.3%
o 1858
 
4.9%
c 1718
 
4.6%
Other values (43) 11533
30.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 30020
79.6%
Uppercase Letter 3900
 
10.3%
Space Separator 3400
 
9.0%
Other Punctuation 274
 
0.7%
Dash Punctuation 47
 
0.1%
Open Punctuation 46
 
0.1%
Close Punctuation 46
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 3629
12.1%
i 2876
9.6%
r 2821
9.4%
n 2815
9.4%
t 2656
8.8%
a 2427
8.1%
s 2000
 
6.7%
o 1858
 
6.2%
c 1718
 
5.7%
l 1572
 
5.2%
Other values (16) 5648
18.8%
Uppercase Letter
ValueCountFrequency (%)
S 759
19.5%
C 556
14.3%
A 332
8.5%
O 295
 
7.6%
P 285
 
7.3%
M 242
 
6.2%
E 196
 
5.0%
R 194
 
5.0%
T 151
 
3.9%
I 130
 
3.3%
Other values (11) 760
19.5%
Other Punctuation
ValueCountFrequency (%)
, 271
98.9%
' 3
 
1.1%
Space Separator
ValueCountFrequency (%)
3400
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 33920
89.9%
Common 3813
 
10.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3629
 
10.7%
i 2876
 
8.5%
r 2821
 
8.3%
n 2815
 
8.3%
t 2656
 
7.8%
a 2427
 
7.2%
s 2000
 
5.9%
o 1858
 
5.5%
c 1718
 
5.1%
l 1572
 
4.6%
Other values (37) 9548
28.1%
Common
ValueCountFrequency (%)
3400
89.2%
, 271
 
7.1%
- 47
 
1.2%
( 46
 
1.2%
) 46
 
1.2%
' 3
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37733
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 3629
 
9.6%
3400
 
9.0%
i 2876
 
7.6%
r 2821
 
7.5%
n 2815
 
7.5%
t 2656
 
7.0%
a 2427
 
6.4%
s 2000
 
5.3%
o 1858
 
4.9%
c 1718
 
4.6%
Other values (43) 11533
30.6%

types_of_construction_projects_performed
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB
Distinct883
Distinct (%)88.3%
Missing0
Missing (%)0.0%
Memory size94.1 KiB
2023-12-09T23:12:46.633446image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length797
Median length653
Mean length39.19
Min length3

Characters and Unicode

Total characters39190
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique828 ?
Unique (%)82.8%

Sample

1st row37003
2nd row91800 | 92500
3rd row39356
4th row48500
5th row94845
ValueCountFrequency (%)
4275
44.8%
91800 74
 
0.8%
91200 46
 
0.5%
91455 26
 
0.3%
92400 24
 
0.3%
91872 23
 
0.2%
91548 23
 
0.2%
90607 22
 
0.2%
91461 22
 
0.2%
91841 21
 
0.2%
Other values (2520) 4994
52.3%
2023-12-09T23:12:47.239175image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8550
21.8%
0 4750
12.1%
| 4275
10.9%
9 3738
9.5%
5 2988
 
7.6%
1 2689
 
6.9%
2 2546
 
6.5%
4 2303
 
5.9%
8 2257
 
5.8%
6 1995
 
5.1%
Other values (2) 3099
 
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26365
67.3%
Space Separator 8550
 
21.8%
Math Symbol 4275
 
10.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4750
18.0%
9 3738
14.2%
5 2988
11.3%
1 2689
10.2%
2 2546
9.7%
4 2303
8.7%
8 2257
8.6%
6 1995
7.6%
3 1641
 
6.2%
7 1458
 
5.5%
Space Separator
ValueCountFrequency (%)
8550
100.0%
Math Symbol
ValueCountFrequency (%)
| 4275
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39190
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8550
21.8%
0 4750
12.1%
| 4275
10.9%
9 3738
9.5%
5 2988
 
7.6%
1 2689
 
6.9%
2 2546
 
6.5%
4 2303
 
5.9%
8 2257
 
5.8%
6 1995
 
5.1%
Other values (2) 3099
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39190
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8550
21.8%
0 4750
12.1%
| 4275
10.9%
9 3738
9.5%
5 2988
 
7.6%
1 2689
 
6.9%
2 2546
 
6.5%
4 2303
 
5.9%
8 2257
 
5.8%
6 1995
 
5.1%
Other values (2) 3099
 
7.9%
Distinct907
Distinct (%)94.7%
Missing42
Missing (%)4.2%
Memory size73.3 KiB
2023-12-09T23:12:47.714712image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length91
Median length50
Mean length19.68997912
Min length3

Characters and Unicode

Total characters18863
Distinct characters74
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique875 ?
Unique (%)91.3%

Sample

1st rowRethink
2nd rowWalsh Construction
3rd rowTamara Wilson
4th rowLa Land Baptiste LLC
5th rowJan Jaskot
ValueCountFrequency (%)
of 91
 
3.2%
nyc 68
 
2.4%
inc 66
 
2.3%
construction 64
 
2.3%
55
 
1.9%
llc 53
 
1.9%
new 42
 
1.5%
department 40
 
1.4%
services 36
 
1.3%
york 36
 
1.3%
Other values (1402) 2289
80.6%
2023-12-09T23:12:48.357969image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1885
 
10.0%
e 1402
 
7.4%
o 1200
 
6.4%
n 1185
 
6.3%
t 1116
 
5.9%
r 1056
 
5.6%
a 1009
 
5.3%
i 997
 
5.3%
s 702
 
3.7%
C 613
 
3.2%
Other values (64) 7698
40.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12404
65.8%
Uppercase Letter 4218
 
22.4%
Space Separator 1885
 
10.0%
Other Punctuation 226
 
1.2%
Decimal Number 82
 
0.4%
Dash Punctuation 23
 
0.1%
Open Punctuation 10
 
0.1%
Close Punctuation 10
 
0.1%
Math Symbol 3
 
< 0.1%
Final Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1402
11.3%
o 1200
9.7%
n 1185
9.6%
t 1116
9.0%
r 1056
 
8.5%
a 1009
 
8.1%
i 997
 
8.0%
s 702
 
5.7%
l 581
 
4.7%
c 510
 
4.1%
Other values (16) 2646
21.3%
Uppercase Letter
ValueCountFrequency (%)
C 613
14.5%
S 332
 
7.9%
A 321
 
7.6%
N 273
 
6.5%
L 235
 
5.6%
E 207
 
4.9%
D 200
 
4.7%
H 199
 
4.7%
I 199
 
4.7%
M 193
 
4.6%
Other values (16) 1446
34.3%
Decimal Number
ValueCountFrequency (%)
1 27
32.9%
3 10
 
12.2%
0 10
 
12.2%
2 8
 
9.8%
5 7
 
8.5%
4 6
 
7.3%
9 4
 
4.9%
6 4
 
4.9%
8 3
 
3.7%
7 3
 
3.7%
Other Punctuation
ValueCountFrequency (%)
. 93
41.2%
, 52
23.0%
& 45
19.9%
/ 27
 
11.9%
' 9
 
4.0%
Math Symbol
ValueCountFrequency (%)
+ 2
66.7%
| 1
33.3%
Space Separator
ValueCountFrequency (%)
1885
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Final Punctuation
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 16622
88.1%
Common 2241
 
11.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1402
 
8.4%
o 1200
 
7.2%
n 1185
 
7.1%
t 1116
 
6.7%
r 1056
 
6.4%
a 1009
 
6.1%
i 997
 
6.0%
s 702
 
4.2%
C 613
 
3.7%
l 581
 
3.5%
Other values (42) 6761
40.7%
Common
ValueCountFrequency (%)
1885
84.1%
. 93
 
4.1%
, 52
 
2.3%
& 45
 
2.0%
/ 27
 
1.2%
1 27
 
1.2%
- 23
 
1.0%
3 10
 
0.4%
0 10
 
0.4%
( 10
 
0.4%
Other values (12) 59
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18861
> 99.9%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1885
 
10.0%
e 1402
 
7.4%
o 1200
 
6.4%
n 1185
 
6.3%
t 1116
 
5.9%
r 1056
 
5.6%
a 1009
 
5.3%
i 997
 
5.3%
s 702
 
3.7%
C 613
 
3.3%
Other values (63) 7696
40.8%
Punctuation
ValueCountFrequency (%)
2
100.0%
Distinct654
Distinct (%)69.0%
Missing52
Missing (%)5.2%
Memory size59.7 KiB
2023-12-09T23:12:48.737835image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.581223629
Min length1

Characters and Unicode

Total characters5291
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique545 ?
Unique (%)57.5%

Sample

1st row50000
2nd row273350
3rd row20
4th row200000
5th row150
ValueCountFrequency (%)
5000 14
 
1.5%
500000 12
 
1.3%
20000 10
 
1.1%
50000 10
 
1.1%
250000 10
 
1.1%
200000 10
 
1.1%
300000 9
 
0.9%
100000 9
 
0.9%
150000 9
 
0.9%
400000 8
 
0.8%
Other values (643) 847
89.3%
2023-12-09T23:12:49.236002image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2310
43.7%
1 474
 
9.0%
5 461
 
8.7%
2 391
 
7.4%
7 298
 
5.6%
4 293
 
5.5%
3 282
 
5.3%
8 269
 
5.1%
6 249
 
4.7%
9 218
 
4.1%
Other values (2) 46
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5245
99.1%
Other Punctuation 45
 
0.9%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2310
44.0%
1 474
 
9.0%
5 461
 
8.8%
2 391
 
7.5%
7 298
 
5.7%
4 293
 
5.6%
3 282
 
5.4%
8 269
 
5.1%
6 249
 
4.7%
9 218
 
4.2%
Other Punctuation
ValueCountFrequency (%)
. 45
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5291
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2310
43.7%
1 474
 
9.0%
5 461
 
8.7%
2 391
 
7.4%
7 298
 
5.6%
4 293
 
5.5%
3 282
 
5.3%
8 269
 
5.1%
6 249
 
4.7%
9 218
 
4.1%
Other values (2) 46
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5291
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2310
43.7%
1 474
 
9.0%
5 461
 
8.7%
2 391
 
7.4%
7 298
 
5.6%
4 293
 
5.5%
3 282
 
5.3%
8 269
 
5.1%
6 249
 
4.7%
9 218
 
4.1%
Other values (2) 46
 
0.9%
Distinct30
Distinct (%)3.3%
Missing97
Missing (%)9.7%
Memory size55.9 KiB
2023-12-09T23:12:49.417728image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.782945736
Min length1

Characters and Unicode

Total characters2513
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)1.1%

Sample

1st row100
2nd row100
3rd row100
4th row100
5th row100
ValueCountFrequency (%)
100 727
80.5%
50 26
 
2.9%
90 17
 
1.9%
0 17
 
1.9%
80 14
 
1.6%
75 13
 
1.4%
95 12
 
1.3%
70 10
 
1.1%
20 9
 
1.0%
60 7
 
0.8%
Other values (20) 51
 
5.6%
2023-12-09T23:12:49.737146image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1567
62.4%
1 735
29.2%
5 79
 
3.1%
9 34
 
1.4%
8 25
 
1.0%
7 25
 
1.0%
2 16
 
0.6%
6 14
 
0.6%
3 10
 
0.4%
4 8
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2513
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1567
62.4%
1 735
29.2%
5 79
 
3.1%
9 34
 
1.4%
8 25
 
1.0%
7 25
 
1.0%
2 16
 
0.6%
6 14
 
0.6%
3 10
 
0.4%
4 8
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 2513
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1567
62.4%
1 735
29.2%
5 79
 
3.1%
9 34
 
1.4%
8 25
 
1.0%
7 25
 
1.0%
2 16
 
0.6%
6 14
 
0.6%
3 10
 
0.4%
4 8
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2513
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1567
62.4%
1 735
29.2%
5 79
 
3.1%
9 34
 
1.4%
8 25
 
1.0%
7 25
 
1.0%
2 16
 
0.6%
6 14
 
0.6%
3 10
 
0.4%
4 8
 
0.3%
Distinct706
Distinct (%)73.7%
Missing42
Missing (%)4.2%
Memory size76.3 KiB
2023-12-09T23:12:50.060992image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters22034
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique561 ?
Unique (%)58.6%

Sample

1st row2020-04-01T00:00:00.000
2nd row2020-12-08T00:00:00.000
3rd row2020-10-06T00:00:00.000
4th row2018-01-01T00:00:00.000
5th row2021-05-28T00:00:00.000
ValueCountFrequency (%)
2018-01-01t00:00:00.000 16
 
1.7%
2019-01-01t00:00:00.000 9
 
0.9%
2020-01-01t00:00:00.000 9
 
0.9%
2015-01-01t00:00:00.000 7
 
0.7%
2021-07-01t00:00:00.000 7
 
0.7%
2022-01-01t00:00:00.000 6
 
0.6%
2017-03-01t00:00:00.000 5
 
0.5%
2019-04-01t00:00:00.000 5
 
0.5%
2020-01-15t00:00:00.000 5
 
0.5%
2019-07-01t00:00:00.000 5
 
0.5%
Other values (696) 884
92.3%
2023-12-09T23:12:50.490416image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11043
50.1%
2 1921
 
8.7%
- 1916
 
8.7%
: 1916
 
8.7%
1 1715
 
7.8%
T 958
 
4.3%
. 958
 
4.3%
3 312
 
1.4%
9 294
 
1.3%
8 261
 
1.2%
Other values (4) 740
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16286
73.9%
Other Punctuation 2874
 
13.0%
Dash Punctuation 1916
 
8.7%
Uppercase Letter 958
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11043
67.8%
2 1921
 
11.8%
1 1715
 
10.5%
3 312
 
1.9%
9 294
 
1.8%
8 261
 
1.6%
7 217
 
1.3%
6 186
 
1.1%
4 183
 
1.1%
5 154
 
0.9%
Other Punctuation
ValueCountFrequency (%)
: 1916
66.7%
. 958
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1916
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 958
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21076
95.7%
Latin 958
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11043
52.4%
2 1921
 
9.1%
- 1916
 
9.1%
: 1916
 
9.1%
1 1715
 
8.1%
. 958
 
4.5%
3 312
 
1.5%
9 294
 
1.4%
8 261
 
1.2%
7 217
 
1.0%
Other values (3) 523
 
2.5%
Latin
ValueCountFrequency (%)
T 958
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22034
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11043
50.1%
2 1921
 
8.7%
- 1916
 
8.7%
: 1916
 
8.7%
1 1715
 
7.8%
T 958
 
4.3%
. 958
 
4.3%
3 312
 
1.4%
9 294
 
1.3%
8 261
 
1.2%
Other values (4) 740
 
3.4%
Distinct948
Distinct (%)99.1%
Missing43
Missing (%)4.3%
Memory size111.7 KiB
2023-12-09T23:12:50.880971image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length100
Median length81
Mean length59.68234065
Min length3

Characters and Unicode

Total characters57116
Distinct characters86
Distinct categories13 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique941 ?
Unique (%)98.3%

Sample

1st rowProduce Meals for low income and elderly
2nd rowdesign of initial support design of geotechnical instrumentation, onsite construction management
3rd row024 Inc sold wax melts to the customer Tamara Wilson
4th rowJanitorial.
5th rowHome Health Care
ValueCountFrequency (%)
and 444
 
5.5%
of 175
 
2.2%
the 169
 
2.1%
for 166
 
2.1%
services 133
 
1.7%
to 127
 
1.6%
104
 
1.3%
a 90
 
1.1%
provided 84
 
1.0%
design 69
 
0.9%
Other values (2766) 6484
80.6%
2023-12-09T23:12:51.444093image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7079
 
12.4%
e 4996
 
8.7%
n 3744
 
6.6%
i 3710
 
6.5%
a 3579
 
6.3%
t 3437
 
6.0%
o 3342
 
5.9%
r 3254
 
5.7%
s 2888
 
5.1%
l 2096
 
3.7%
Other values (76) 18991
33.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 43564
76.3%
Space Separator 7079
 
12.4%
Uppercase Letter 4495
 
7.9%
Other Punctuation 1303
 
2.3%
Decimal Number 410
 
0.7%
Dash Punctuation 106
 
0.2%
Control 73
 
0.1%
Open Punctuation 40
 
0.1%
Close Punctuation 33
 
0.1%
Final Punctuation 5
 
< 0.1%
Other values (3) 8
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4996
11.5%
n 3744
 
8.6%
i 3710
 
8.5%
a 3579
 
8.2%
t 3437
 
7.9%
o 3342
 
7.7%
r 3254
 
7.5%
s 2888
 
6.6%
l 2096
 
4.8%
d 2043
 
4.7%
Other values (17) 10475
24.0%
Uppercase Letter
ValueCountFrequency (%)
S 435
 
9.7%
P 386
 
8.6%
A 377
 
8.4%
C 366
 
8.1%
R 323
 
7.2%
E 294
 
6.5%
I 288
 
6.4%
T 256
 
5.7%
D 238
 
5.3%
O 205
 
4.6%
Other values (16) 1327
29.5%
Other Punctuation
ValueCountFrequency (%)
, 694
53.3%
. 404
31.0%
& 62
 
4.8%
/ 59
 
4.5%
' 33
 
2.5%
: 22
 
1.7%
; 8
 
0.6%
# 6
 
0.5%
5
 
0.4%
? 4
 
0.3%
Other values (3) 6
 
0.5%
Decimal Number
ValueCountFrequency (%)
0 90
22.0%
1 81
19.8%
2 71
17.3%
3 41
10.0%
5 36
 
8.8%
4 28
 
6.8%
7 20
 
4.9%
8 15
 
3.7%
6 15
 
3.7%
9 13
 
3.2%
Final Punctuation
ValueCountFrequency (%)
4
80.0%
1
 
20.0%
Space Separator
ValueCountFrequency (%)
7079
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 106
100.0%
Control
ValueCountFrequency (%)
73
100.0%
Open Punctuation
ValueCountFrequency (%)
( 40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Math Symbol
ValueCountFrequency (%)
+ 4
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 3
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 48059
84.1%
Common 9057
 
15.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4996
 
10.4%
n 3744
 
7.8%
i 3710
 
7.7%
a 3579
 
7.4%
t 3437
 
7.2%
o 3342
 
7.0%
r 3254
 
6.8%
s 2888
 
6.0%
l 2096
 
4.4%
d 2043
 
4.3%
Other values (43) 14970
31.1%
Common
ValueCountFrequency (%)
7079
78.2%
, 694
 
7.7%
. 404
 
4.5%
- 106
 
1.2%
0 90
 
1.0%
1 81
 
0.9%
73
 
0.8%
2 71
 
0.8%
& 62
 
0.7%
/ 59
 
0.7%
Other values (23) 338
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57101
> 99.9%
Punctuation 11
 
< 0.1%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7079
 
12.4%
e 4996
 
8.7%
n 3744
 
6.6%
i 3710
 
6.5%
a 3579
 
6.3%
t 3437
 
6.0%
o 3342
 
5.9%
r 3254
 
5.7%
s 2888
 
5.1%
l 2096
 
3.7%
Other values (71) 18976
33.2%
Punctuation
ValueCountFrequency (%)
5
45.5%
4
36.4%
1
 
9.1%
1
 
9.1%
None
ValueCountFrequency (%)
ç 4
100.0%
Distinct766
Distinct (%)97.1%
Missing211
Missing (%)21.1%
Memory size66.3 KiB
2023-12-09T23:12:51.843534image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length100
Median length48
Mean length20.02281369
Min length2

Characters and Unicode

Total characters15798
Distinct characters78
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique748 ?
Unique (%)94.8%

Sample

1st rowDanielle Warr
2nd rowLiddso
3rd rowHelena Zak
4th rowTruline Construction Services Inc
5th rowGlito Corp
ValueCountFrequency (%)
inc 67
 
2.8%
of 63
 
2.7%
construction 51
 
2.2%
nyc 42
 
1.8%
40
 
1.7%
llc 39
 
1.7%
new 32
 
1.4%
york 28
 
1.2%
corp 22
 
0.9%
and 22
 
0.9%
Other values (1229) 1957
82.8%
2023-12-09T23:12:52.419310image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1578
 
10.0%
e 1215
 
7.7%
n 1027
 
6.5%
o 974
 
6.2%
r 912
 
5.8%
t 897
 
5.7%
i 870
 
5.5%
a 830
 
5.3%
s 554
 
3.5%
l 533
 
3.4%
Other values (68) 6408
40.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10527
66.6%
Uppercase Letter 3347
 
21.2%
Space Separator 1578
 
10.0%
Other Punctuation 191
 
1.2%
Decimal Number 103
 
0.7%
Dash Punctuation 24
 
0.2%
Close Punctuation 12
 
0.1%
Open Punctuation 12
 
0.1%
Final Punctuation 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1215
11.5%
n 1027
9.8%
o 974
9.3%
r 912
8.7%
t 897
 
8.5%
i 870
 
8.3%
a 830
 
7.9%
s 554
 
5.3%
l 533
 
5.1%
c 470
 
4.5%
Other values (16) 2245
21.3%
Uppercase Letter
ValueCountFrequency (%)
C 476
14.2%
S 266
 
7.9%
A 234
 
7.0%
N 225
 
6.7%
M 171
 
5.1%
I 167
 
5.0%
L 164
 
4.9%
D 160
 
4.8%
P 159
 
4.8%
R 154
 
4.6%
Other values (16) 1171
35.0%
Decimal Number
ValueCountFrequency (%)
2 24
23.3%
1 23
22.3%
0 11
10.7%
5 9
 
8.7%
3 8
 
7.8%
7 7
 
6.8%
4 6
 
5.8%
6 6
 
5.8%
9 5
 
4.9%
8 4
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 82
42.9%
, 42
22.0%
& 37
19.4%
/ 21
 
11.0%
' 7
 
3.7%
: 1
 
0.5%
! 1
 
0.5%
Dash Punctuation
ValueCountFrequency (%)
- 23
95.8%
1
 
4.2%
Final Punctuation
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
1578
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13874
87.8%
Common 1924
 
12.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1215
 
8.8%
n 1027
 
7.4%
o 974
 
7.0%
r 912
 
6.6%
t 897
 
6.5%
i 870
 
6.3%
a 830
 
6.0%
s 554
 
4.0%
l 533
 
3.8%
C 476
 
3.4%
Other values (42) 5586
40.3%
Common
ValueCountFrequency (%)
1578
82.0%
. 82
 
4.3%
, 42
 
2.2%
& 37
 
1.9%
2 24
 
1.2%
1 23
 
1.2%
- 23
 
1.2%
/ 21
 
1.1%
) 12
 
0.6%
( 12
 
0.6%
Other values (16) 70
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15794
> 99.9%
Punctuation 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1578
 
10.0%
e 1215
 
7.7%
n 1027
 
6.5%
o 974
 
6.2%
r 912
 
5.8%
t 897
 
5.7%
i 870
 
5.5%
a 830
 
5.3%
s 554
 
3.5%
l 533
 
3.4%
Other values (64) 6404
40.5%
Punctuation
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Distinct541
Distinct (%)70.0%
Missing227
Missing (%)22.7%
Memory size54.1 KiB
2023-12-09T23:12:52.835329image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.058214748
Min length1

Characters and Unicode

Total characters3910
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique455 ?
Unique (%)58.9%

Sample

1st row10
2nd row200000
3rd row100
4th row3938
5th row7000
ValueCountFrequency (%)
5000 17
 
2.2%
10000 13
 
1.7%
20000 10
 
1.3%
40000 8
 
1.0%
50000 8
 
1.0%
100000 8
 
1.0%
500 7
 
0.9%
4000 7
 
0.9%
100 7
 
0.9%
30000 7
 
0.9%
Other values (531) 681
88.1%
2023-12-09T23:12:53.392291image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1640
41.9%
1 377
 
9.6%
5 367
 
9.4%
2 289
 
7.4%
3 239
 
6.1%
4 232
 
5.9%
7 202
 
5.2%
8 176
 
4.5%
9 176
 
4.5%
6 169
 
4.3%
Other values (2) 43
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3867
98.9%
Other Punctuation 42
 
1.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1640
42.4%
1 377
 
9.7%
5 367
 
9.5%
2 289
 
7.5%
3 239
 
6.2%
4 232
 
6.0%
7 202
 
5.2%
8 176
 
4.6%
9 176
 
4.6%
6 169
 
4.4%
Other Punctuation
ValueCountFrequency (%)
. 42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3910
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1640
41.9%
1 377
 
9.6%
5 367
 
9.4%
2 289
 
7.4%
3 239
 
6.1%
4 232
 
5.9%
7 202
 
5.2%
8 176
 
4.5%
9 176
 
4.5%
6 169
 
4.3%
Other values (2) 43
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3910
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1640
41.9%
1 377
 
9.6%
5 367
 
9.4%
2 289
 
7.4%
3 239
 
6.1%
4 232
 
5.9%
7 202
 
5.2%
8 176
 
4.5%
9 176
 
4.5%
6 169
 
4.3%
Other values (2) 43
 
1.1%
Distinct23
Distinct (%)3.1%
Missing262
Missing (%)26.2%
Memory size51.4 KiB
2023-12-09T23:12:53.561237image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.841463415
Min length1

Characters and Unicode

Total characters2097
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)0.9%

Sample

1st row100
2nd row100
3rd row100
4th row100
5th row100
ValueCountFrequency (%)
100 632
85.6%
50 11
 
1.5%
80 10
 
1.4%
20 10
 
1.4%
75 9
 
1.2%
0 9
 
1.2%
90 9
 
1.2%
85 7
 
0.9%
95 7
 
0.9%
10 6
 
0.8%
Other values (13) 28
 
3.8%
2023-12-09T23:12:53.848486image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1331
63.5%
1 640
30.5%
5 44
 
2.1%
8 19
 
0.9%
2 18
 
0.9%
9 16
 
0.8%
7 12
 
0.6%
3 9
 
0.4%
6 8
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2097
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1331
63.5%
1 640
30.5%
5 44
 
2.1%
8 19
 
0.9%
2 18
 
0.9%
9 16
 
0.8%
7 12
 
0.6%
3 9
 
0.4%
6 8
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 2097
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1331
63.5%
1 640
30.5%
5 44
 
2.1%
8 19
 
0.9%
2 18
 
0.9%
9 16
 
0.8%
7 12
 
0.6%
3 9
 
0.4%
6 8
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2097
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1331
63.5%
1 640
30.5%
5 44
 
2.1%
8 19
 
0.9%
2 18
 
0.9%
9 16
 
0.8%
7 12
 
0.6%
3 9
 
0.4%
6 8
 
0.4%
Distinct596
Distinct (%)75.5%
Missing211
Missing (%)21.1%
Memory size68.4 KiB
2023-12-09T23:12:54.140607image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters18147
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique475 ?
Unique (%)60.2%

Sample

1st row2020-09-23T00:00:00.000
2nd row2018-01-01T00:00:00.000
3rd row2021-06-08T00:00:00.000
4th row2019-03-12T00:00:00.000
5th row2020-06-27T00:00:00.000
ValueCountFrequency (%)
2018-01-01t00:00:00.000 10
 
1.3%
2019-02-01t00:00:00.000 5
 
0.6%
2013-01-01t00:00:00.000 5
 
0.6%
2015-01-01t00:00:00.000 5
 
0.6%
2023-01-01t00:00:00.000 5
 
0.6%
2021-12-31t00:00:00.000 5
 
0.6%
2018-12-01t00:00:00.000 5
 
0.6%
2017-01-01t00:00:00.000 4
 
0.5%
2019-01-01t00:00:00.000 4
 
0.5%
2021-09-01t00:00:00.000 4
 
0.5%
Other values (586) 737
93.4%
2023-12-09T23:12:54.564156image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9135
50.3%
2 1644
 
9.1%
- 1578
 
8.7%
: 1578
 
8.7%
1 1287
 
7.1%
T 789
 
4.3%
. 789
 
4.3%
9 249
 
1.4%
3 248
 
1.4%
8 236
 
1.3%
Other values (4) 614
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13413
73.9%
Other Punctuation 2367
 
13.0%
Dash Punctuation 1578
 
8.7%
Uppercase Letter 789
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9135
68.1%
2 1644
 
12.3%
1 1287
 
9.6%
9 249
 
1.9%
3 248
 
1.8%
8 236
 
1.8%
7 182
 
1.4%
5 159
 
1.2%
6 146
 
1.1%
4 127
 
0.9%
Other Punctuation
ValueCountFrequency (%)
: 1578
66.7%
. 789
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1578
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 789
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17358
95.7%
Latin 789
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9135
52.6%
2 1644
 
9.5%
- 1578
 
9.1%
: 1578
 
9.1%
1 1287
 
7.4%
. 789
 
4.5%
9 249
 
1.4%
3 248
 
1.4%
8 236
 
1.4%
7 182
 
1.0%
Other values (3) 432
 
2.5%
Latin
ValueCountFrequency (%)
T 789
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18147
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9135
50.3%
2 1644
 
9.1%
- 1578
 
8.7%
: 1578
 
8.7%
1 1287
 
7.1%
T 789
 
4.3%
. 789
 
4.3%
9 249
 
1.4%
3 248
 
1.4%
8 236
 
1.3%
Other values (4) 614
 
3.4%
Distinct782
Distinct (%)99.1%
Missing211
Missing (%)21.1%
Memory size95.2 KiB
2023-12-09T23:12:54.958704image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length100
Median length79
Mean length56.14321926
Min length2

Characters and Unicode

Total characters44297
Distinct characters90
Distinct categories13 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique777 ?
Unique (%)98.5%

Sample

1st row024 Inc sold wax melts to the customer Danielle Warr
2nd rowBuilding maintenance
3rd rowHome Health Care
4th rowProvided construction management consulting services for converting a parking structure into the cha
5th rowDesign consultation, construction documents, city agency submission and construction progress inspec
ValueCountFrequency (%)
and 346
 
5.5%
of 144
 
2.3%
for 120
 
1.9%
the 114
 
1.8%
to 106
 
1.7%
services 93
 
1.5%
88
 
1.4%
a 67
 
1.1%
provided 54
 
0.9%
design 51
 
0.8%
Other values (2360) 5104
81.2%
2023-12-09T23:12:55.542994image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5474
 
12.4%
e 3804
 
8.6%
n 3003
 
6.8%
i 2902
 
6.6%
a 2796
 
6.3%
t 2741
 
6.2%
o 2578
 
5.8%
r 2468
 
5.6%
s 2149
 
4.9%
l 1637
 
3.7%
Other values (80) 14745
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 33616
75.9%
Space Separator 5474
 
12.4%
Uppercase Letter 3742
 
8.4%
Other Punctuation 935
 
2.1%
Decimal Number 321
 
0.7%
Dash Punctuation 84
 
0.2%
Control 61
 
0.1%
Open Punctuation 26
 
0.1%
Close Punctuation 24
 
0.1%
Final Punctuation 7
 
< 0.1%
Other values (3) 7
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 3804
11.3%
n 3003
 
8.9%
i 2902
 
8.6%
a 2796
 
8.3%
t 2741
 
8.2%
o 2578
 
7.7%
r 2468
 
7.3%
s 2149
 
6.4%
l 1637
 
4.9%
d 1463
 
4.4%
Other values (17) 8075
24.0%
Uppercase Letter
ValueCountFrequency (%)
S 370
 
9.9%
P 316
 
8.4%
A 311
 
8.3%
C 286
 
7.6%
E 260
 
6.9%
I 257
 
6.9%
R 242
 
6.5%
T 217
 
5.8%
D 209
 
5.6%
N 163
 
4.4%
Other values (16) 1111
29.7%
Other Punctuation
ValueCountFrequency (%)
, 454
48.6%
. 330
35.3%
& 55
 
5.9%
/ 39
 
4.2%
: 20
 
2.1%
' 19
 
2.0%
; 5
 
0.5%
# 4
 
0.4%
? 4
 
0.4%
2
 
0.2%
Other values (3) 3
 
0.3%
Decimal Number
ValueCountFrequency (%)
0 92
28.7%
1 58
18.1%
2 54
16.8%
5 27
 
8.4%
3 25
 
7.8%
4 22
 
6.9%
6 15
 
4.7%
8 12
 
3.7%
9 11
 
3.4%
7 5
 
1.6%
Math Symbol
ValueCountFrequency (%)
+ 2
40.0%
> 1
20.0%
< 1
20.0%
~ 1
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 82
97.6%
2
 
2.4%
Final Punctuation
ValueCountFrequency (%)
5
71.4%
2
 
28.6%
Space Separator
ValueCountFrequency (%)
5474
100.0%
Control
ValueCountFrequency (%)
61
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 37358
84.3%
Common 6939
 
15.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3804
 
10.2%
n 3003
 
8.0%
i 2902
 
7.8%
a 2796
 
7.5%
t 2741
 
7.3%
o 2578
 
6.9%
r 2468
 
6.6%
s 2149
 
5.8%
l 1637
 
4.4%
d 1463
 
3.9%
Other values (43) 11817
31.6%
Common
ValueCountFrequency (%)
5474
78.9%
, 454
 
6.5%
. 330
 
4.8%
0 92
 
1.3%
- 82
 
1.2%
61
 
0.9%
1 58
 
0.8%
& 55
 
0.8%
2 54
 
0.8%
/ 39
 
0.6%
Other values (27) 240
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44283
> 99.9%
Punctuation 11
 
< 0.1%
None 2
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5474
 
12.4%
e 3804
 
8.6%
n 3003
 
6.8%
i 2902
 
6.6%
a 2796
 
6.3%
t 2741
 
6.2%
o 2578
 
5.8%
r 2468
 
5.6%
s 2149
 
4.9%
l 1637
 
3.7%
Other values (73) 14731
33.3%
Punctuation
ValueCountFrequency (%)
5
45.5%
2
 
18.2%
2
 
18.2%
2
 
18.2%
None
ValueCountFrequency (%)
é 1
50.0%
¿ 1
50.0%
Letterlike Symbols
ValueCountFrequency (%)
1
100.0%
Distinct657
Distinct (%)97.8%
Missing328
Missing (%)32.8%
Memory size60.8 KiB
2023-12-09T23:12:55.927264image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length75
Median length44
Mean length19.76339286
Min length3

Characters and Unicode

Total characters13281
Distinct characters73
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique645 ?
Unique (%)96.0%

Sample

1st rowDaidralyn Wood
2nd rowMaimonides Medical Center
3rd rowRhea King
4th rowIrene Gottlieb
5th rowRobert Leo
ValueCountFrequency (%)
construction 53
 
2.7%
of 51
 
2.6%
inc 46
 
2.3%
44
 
2.2%
nyc 39
 
2.0%
llc 25
 
1.3%
corp 25
 
1.3%
new 23
 
1.2%
and 19
 
1.0%
york 18
 
0.9%
Other values (1136) 1652
82.8%
2023-12-09T23:12:56.504521image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1328
 
10.0%
e 968
 
7.3%
n 906
 
6.8%
o 854
 
6.4%
t 833
 
6.3%
r 752
 
5.7%
a 742
 
5.6%
i 730
 
5.5%
s 445
 
3.4%
C 431
 
3.2%
Other values (63) 5292
39.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8824
66.4%
Uppercase Letter 2856
 
21.5%
Space Separator 1328
 
10.0%
Other Punctuation 167
 
1.3%
Decimal Number 65
 
0.5%
Dash Punctuation 26
 
0.2%
Open Punctuation 7
 
0.1%
Close Punctuation 7
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 968
11.0%
n 906
10.3%
o 854
9.7%
t 833
9.4%
r 752
8.5%
a 742
8.4%
i 730
 
8.3%
s 445
 
5.0%
l 390
 
4.4%
c 362
 
4.1%
Other values (16) 1842
20.9%
Uppercase Letter
ValueCountFrequency (%)
C 431
15.1%
S 249
 
8.7%
A 202
 
7.1%
N 183
 
6.4%
M 159
 
5.6%
D 149
 
5.2%
I 137
 
4.8%
L 135
 
4.7%
R 125
 
4.4%
P 123
 
4.3%
Other values (16) 963
33.7%
Decimal Number
ValueCountFrequency (%)
2 13
20.0%
4 8
12.3%
3 8
12.3%
5 8
12.3%
1 7
10.8%
9 6
9.2%
6 6
9.2%
0 3
 
4.6%
8 3
 
4.6%
7 3
 
4.6%
Other Punctuation
ValueCountFrequency (%)
. 70
41.9%
& 37
22.2%
, 35
21.0%
/ 14
 
8.4%
' 11
 
6.6%
Dash Punctuation
ValueCountFrequency (%)
- 25
96.2%
1
 
3.8%
Space Separator
ValueCountFrequency (%)
1328
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11680
87.9%
Common 1601
 
12.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 968
 
8.3%
n 906
 
7.8%
o 854
 
7.3%
t 833
 
7.1%
r 752
 
6.4%
a 742
 
6.4%
i 730
 
6.2%
s 445
 
3.8%
C 431
 
3.7%
l 390
 
3.3%
Other values (42) 4629
39.6%
Common
ValueCountFrequency (%)
1328
82.9%
. 70
 
4.4%
& 37
 
2.3%
, 35
 
2.2%
- 25
 
1.6%
/ 14
 
0.9%
2 13
 
0.8%
' 11
 
0.7%
4 8
 
0.5%
3 8
 
0.5%
Other values (11) 52
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13280
> 99.9%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1328
 
10.0%
e 968
 
7.3%
n 906
 
6.8%
o 854
 
6.4%
t 833
 
6.3%
r 752
 
5.7%
a 742
 
5.6%
i 730
 
5.5%
s 445
 
3.4%
C 431
 
3.2%
Other values (62) 5291
39.8%
Punctuation
ValueCountFrequency (%)
1
100.0%
Distinct472
Distinct (%)72.0%
Missing344
Missing (%)34.4%
Memory size50.7 KiB
2023-12-09T23:12:56.908575image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.150914634
Min length1

Characters and Unicode

Total characters3379
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique393 ?
Unique (%)59.9%

Sample

1st row10
2nd row150000
3rd row100
4th row4665
5th row8000
ValueCountFrequency (%)
20000 9
 
1.4%
5000 9
 
1.4%
100000 9
 
1.4%
2000 9
 
1.4%
150000 8
 
1.2%
25000 7
 
1.1%
100 7
 
1.1%
400000 7
 
1.1%
15000 6
 
0.9%
30000 6
 
0.9%
Other values (462) 579
88.3%
2023-12-09T23:12:57.456672image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1470
43.5%
1 320
 
9.5%
5 313
 
9.3%
2 279
 
8.3%
3 180
 
5.3%
6 177
 
5.2%
4 164
 
4.9%
7 162
 
4.8%
8 149
 
4.4%
9 134
 
4.0%
Other values (2) 31
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3348
99.1%
Other Punctuation 30
 
0.9%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1470
43.9%
1 320
 
9.6%
5 313
 
9.3%
2 279
 
8.3%
3 180
 
5.4%
6 177
 
5.3%
4 164
 
4.9%
7 162
 
4.8%
8 149
 
4.5%
9 134
 
4.0%
Other Punctuation
ValueCountFrequency (%)
. 30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3379
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1470
43.5%
1 320
 
9.5%
5 313
 
9.3%
2 279
 
8.3%
3 180
 
5.3%
6 177
 
5.2%
4 164
 
4.9%
7 162
 
4.8%
8 149
 
4.4%
9 134
 
4.0%
Other values (2) 31
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3379
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1470
43.5%
1 320
 
9.5%
5 313
 
9.3%
2 279
 
8.3%
3 180
 
5.3%
6 177
 
5.2%
4 164
 
4.9%
7 162
 
4.8%
8 149
 
4.4%
9 134
 
4.0%
Other values (2) 31
 
0.9%
Distinct24
Distinct (%)3.9%
Missing387
Missing (%)38.7%
Memory size48.1 KiB
2023-12-09T23:12:57.634925image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.859706362
Min length1

Characters and Unicode

Total characters1753
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)1.1%

Sample

1st row100
2nd row100
3rd row100
4th row100
5th row100
ValueCountFrequency (%)
100 534
87.1%
80 9
 
1.5%
90 9
 
1.5%
75 7
 
1.1%
50 7
 
1.1%
0 6
 
1.0%
70 5
 
0.8%
85 4
 
0.7%
40 4
 
0.7%
10 4
 
0.7%
Other values (14) 24
 
3.9%
2023-12-09T23:12:57.937370image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1119
63.8%
1 540
30.8%
5 28
 
1.6%
9 15
 
0.9%
8 15
 
0.9%
7 13
 
0.7%
3 7
 
0.4%
6 6
 
0.3%
2 6
 
0.3%
4 4
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1753
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1119
63.8%
1 540
30.8%
5 28
 
1.6%
9 15
 
0.9%
8 15
 
0.9%
7 13
 
0.7%
3 7
 
0.4%
6 6
 
0.3%
2 6
 
0.3%
4 4
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 1753
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1119
63.8%
1 540
30.8%
5 28
 
1.6%
9 15
 
0.9%
8 15
 
0.9%
7 13
 
0.7%
3 7
 
0.4%
6 6
 
0.3%
2 6
 
0.3%
4 4
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1753
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1119
63.8%
1 540
30.8%
5 28
 
1.6%
9 15
 
0.9%
8 15
 
0.9%
7 13
 
0.7%
3 7
 
0.4%
6 6
 
0.3%
2 6
 
0.3%
4 4
 
0.2%
Distinct519
Distinct (%)77.2%
Missing328
Missing (%)32.8%
Memory size62.9 KiB
2023-12-09T23:12:58.230405image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters15456
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique420 ?
Unique (%)62.5%

Sample

1st row2020-08-07T00:00:00.000
2nd row2018-01-01T00:00:00.000
3rd row2021-06-01T00:00:00.000
4th row2019-02-10T00:00:00.000
5th row2020-06-01T00:00:00.000
ValueCountFrequency (%)
2018-01-01t00:00:00.000 10
 
1.5%
2019-01-01t00:00:00.000 8
 
1.2%
2017-01-01t00:00:00.000 7
 
1.0%
2020-01-01t00:00:00.000 5
 
0.7%
2014-01-01t00:00:00.000 5
 
0.7%
2018-03-01t00:00:00.000 5
 
0.7%
2016-01-01t00:00:00.000 4
 
0.6%
2017-06-01t00:00:00.000 4
 
0.6%
2016-11-01t00:00:00.000 4
 
0.6%
2014-09-01t00:00:00.000 3
 
0.4%
Other values (509) 617
91.8%
2023-12-09T23:12:58.642370image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7772
50.3%
- 1344
 
8.7%
: 1344
 
8.7%
2 1255
 
8.1%
1 1226
 
7.9%
T 672
 
4.3%
. 672
 
4.3%
8 214
 
1.4%
3 194
 
1.3%
9 187
 
1.2%
Other values (4) 576
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11424
73.9%
Other Punctuation 2016
 
13.0%
Dash Punctuation 1344
 
8.7%
Uppercase Letter 672
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7772
68.0%
2 1255
 
11.0%
1 1226
 
10.7%
8 214
 
1.9%
3 194
 
1.7%
9 187
 
1.6%
7 164
 
1.4%
6 146
 
1.3%
5 135
 
1.2%
4 131
 
1.1%
Other Punctuation
ValueCountFrequency (%)
: 1344
66.7%
. 672
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1344
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 672
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14784
95.7%
Latin 672
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7772
52.6%
- 1344
 
9.1%
: 1344
 
9.1%
2 1255
 
8.5%
1 1226
 
8.3%
. 672
 
4.5%
8 214
 
1.4%
3 194
 
1.3%
9 187
 
1.3%
7 164
 
1.1%
Other values (3) 412
 
2.8%
Latin
ValueCountFrequency (%)
T 672
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15456
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7772
50.3%
- 1344
 
8.7%
: 1344
 
8.7%
2 1255
 
8.1%
1 1226
 
7.9%
T 672
 
4.3%
. 672
 
4.3%
8 214
 
1.4%
3 194
 
1.3%
9 187
 
1.2%
Other values (4) 576
 
3.7%
Distinct669
Distinct (%)99.6%
Missing328
Missing (%)32.8%
Memory size87.1 KiB
2023-12-09T23:12:58.964838image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length100
Median length82
Mean length58.28869048
Min length3

Characters and Unicode

Total characters39170
Distinct characters90
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique667 ?
Unique (%)99.3%

Sample

1st row024 Inc sold wax melts to the customer Daidralyn Wood
2nd rowBuilding maintenance, janitorial.
3rd rowHome Health Care
4th rowProvided construction management services.
5th rowDesign consultation, Construction documentation, city agency application and construction progress i
ValueCountFrequency (%)
and 314
 
5.7%
of 141
 
2.5%
for 109
 
2.0%
the 98
 
1.8%
86
 
1.6%
to 83
 
1.5%
services 79
 
1.4%
design 55
 
1.0%
in 53
 
1.0%
a 46
 
0.8%
Other values (2131) 4469
80.8%
2023-12-09T23:12:59.474531image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4833
 
12.3%
e 3328
 
8.5%
n 2650
 
6.8%
i 2623
 
6.7%
t 2416
 
6.2%
a 2386
 
6.1%
o 2375
 
6.1%
r 2253
 
5.8%
s 1901
 
4.9%
l 1456
 
3.7%
Other values (80) 12949
33.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 29919
76.4%
Space Separator 4833
 
12.3%
Uppercase Letter 3063
 
7.8%
Other Punctuation 887
 
2.3%
Decimal Number 289
 
0.7%
Dash Punctuation 70
 
0.2%
Control 52
 
0.1%
Open Punctuation 25
 
0.1%
Close Punctuation 20
 
0.1%
Final Punctuation 6
 
< 0.1%
Other values (2) 6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 3328
11.1%
n 2650
 
8.9%
i 2623
 
8.8%
t 2416
 
8.1%
a 2386
 
8.0%
o 2375
 
7.9%
r 2253
 
7.5%
s 1901
 
6.4%
l 1456
 
4.9%
d 1308
 
4.4%
Other values (16) 7223
24.1%
Uppercase Letter
ValueCountFrequency (%)
S 291
 
9.5%
A 253
 
8.3%
P 249
 
8.1%
C 240
 
7.8%
E 219
 
7.1%
I 209
 
6.8%
R 199
 
6.5%
T 197
 
6.4%
D 182
 
5.9%
N 142
 
4.6%
Other values (16) 882
28.8%
Other Punctuation
ValueCountFrequency (%)
, 443
49.9%
. 279
31.5%
& 58
 
6.5%
/ 48
 
5.4%
: 17
 
1.9%
; 14
 
1.6%
' 12
 
1.4%
4
 
0.5%
# 4
 
0.5%
" 3
 
0.3%
Other values (3) 5
 
0.6%
Decimal Number
ValueCountFrequency (%)
0 72
24.9%
2 52
18.0%
1 48
16.6%
5 25
 
8.7%
4 24
 
8.3%
3 23
 
8.0%
6 15
 
5.2%
7 12
 
4.2%
9 10
 
3.5%
8 8
 
2.8%
Math Symbol
ValueCountFrequency (%)
+ 2
40.0%
= 1
20.0%
< 1
20.0%
> 1
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 68
97.1%
1
 
1.4%
1
 
1.4%
Open Punctuation
ValueCountFrequency (%)
( 24
96.0%
[ 1
 
4.0%
Final Punctuation
ValueCountFrequency (%)
5
83.3%
1
 
16.7%
Space Separator
ValueCountFrequency (%)
4833
100.0%
Control
ValueCountFrequency (%)
52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 32982
84.2%
Common 6188
 
15.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3328
 
10.1%
n 2650
 
8.0%
i 2623
 
8.0%
t 2416
 
7.3%
a 2386
 
7.2%
o 2375
 
7.2%
r 2253
 
6.8%
s 1901
 
5.8%
l 1456
 
4.4%
d 1308
 
4.0%
Other values (42) 10286
31.2%
Common
ValueCountFrequency (%)
4833
78.1%
, 443
 
7.2%
. 279
 
4.5%
0 72
 
1.2%
- 68
 
1.1%
& 58
 
0.9%
52
 
0.8%
2 52
 
0.8%
1 48
 
0.8%
/ 48
 
0.8%
Other values (28) 235
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39158
> 99.9%
Punctuation 12
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4833
 
12.3%
e 3328
 
8.5%
n 2650
 
6.8%
i 2623
 
6.7%
t 2416
 
6.2%
a 2386
 
6.1%
o 2375
 
6.1%
r 2253
 
5.8%
s 1901
 
4.9%
l 1456
 
3.7%
Other values (75) 12937
33.0%
Punctuation
ValueCountFrequency (%)
5
41.7%
4
33.3%
1
 
8.3%
1
 
8.3%
1
 
8.3%

capacity_building_programs
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size58.6 KiB
2023-12-09T23:12:59.607030image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.838
Min length2

Characters and Unicode

Total characters2838
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowNo
4th rowYes
5th rowYes
ValueCountFrequency (%)
yes 838
83.8%
no 162
 
16.2%
2023-12-09T23:12:59.835662image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 838
29.5%
e 838
29.5%
s 838
29.5%
N 162
 
5.7%
o 162
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1838
64.8%
Uppercase Letter 1000
35.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 838
45.6%
s 838
45.6%
o 162
 
8.8%
Uppercase Letter
ValueCountFrequency (%)
Y 838
83.8%
N 162
 
16.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 2838
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 838
29.5%
e 838
29.5%
s 838
29.5%
N 162
 
5.7%
o 162
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2838
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 838
29.5%
e 838
29.5%
s 838
29.5%
N 162
 
5.7%
o 162
 
5.7%

borough
Text

MISSING 

Distinct5
Distinct (%)0.8%
Missing380
Missing (%)38.0%
Memory size51.0 KiB
2023-12-09T23:13:00.003871image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length8
Mean length7.403225806
Min length5

Characters and Unicode

Total characters4590
Distinct characters18
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBROOKLYN
2nd rowBRONX
3rd rowBROOKLYN
4th rowBROOKLYN
5th rowMANHATTAN
ValueCountFrequency (%)
queens 182
28.2%
brooklyn 180
27.9%
manhattan 166
25.7%
bronx 66
 
10.2%
staten 26
 
4.0%
is 26
 
4.0%
2023-12-09T23:13:00.336432image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 786
17.1%
A 524
11.4%
O 426
9.3%
E 390
 
8.5%
T 384
 
8.4%
B 246
 
5.4%
R 246
 
5.4%
S 234
 
5.1%
Q 182
 
4.0%
U 182
 
4.0%
Other values (8) 990
21.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 4564
99.4%
Space Separator 26
 
0.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 786
17.2%
A 524
11.5%
O 426
9.3%
E 390
8.5%
T 384
 
8.4%
B 246
 
5.4%
R 246
 
5.4%
S 234
 
5.1%
Q 182
 
4.0%
U 182
 
4.0%
Other values (7) 964
21.1%
Space Separator
ValueCountFrequency (%)
26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4564
99.4%
Common 26
 
0.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 786
17.2%
A 524
11.5%
O 426
9.3%
E 390
8.5%
T 384
 
8.4%
B 246
 
5.4%
R 246
 
5.4%
S 234
 
5.1%
Q 182
 
4.0%
U 182
 
4.0%
Other values (7) 964
21.1%
Common
ValueCountFrequency (%)
26
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4590
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 786
17.1%
A 524
11.4%
O 426
9.3%
E 390
 
8.5%
T 384
 
8.4%
B 246
 
5.4%
R 246
 
5.4%
S 234
 
5.1%
Q 182
 
4.0%
U 182
 
4.0%
Other values (8) 990
21.6%

latitude
Text

MISSING 

Distinct597
Distinct (%)96.3%
Missing380
Missing (%)38.0%
Memory size51.9 KiB
2023-12-09T23:13:00.735034image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.888709677
Min length6

Characters and Unicode

Total characters5511
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique575 ?
Unique (%)92.7%

Sample

1st row40.714065
2nd row40.863508
3rd row40.680772
4th row40.703905
5th row40.763365
ValueCountFrequency (%)
40.74306 3
 
0.5%
40.588719 2
 
0.3%
40.815214 2
 
0.3%
40.665271 2
 
0.3%
40.750564 2
 
0.3%
40.717612 2
 
0.3%
40.71013 2
 
0.3%
40.656142 2
 
0.3%
40.739873 2
 
0.3%
40.746091 2
 
0.3%
Other values (587) 599
96.6%
2023-12-09T23:13:01.260973image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 913
16.6%
0 897
16.3%
. 620
11.3%
7 576
10.5%
6 509
9.2%
8 387
7.0%
5 359
 
6.5%
1 332
 
6.0%
9 325
 
5.9%
3 306
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4891
88.7%
Other Punctuation 620
 
11.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 913
18.7%
0 897
18.3%
7 576
11.8%
6 509
10.4%
8 387
7.9%
5 359
 
7.3%
1 332
 
6.8%
9 325
 
6.6%
3 306
 
6.3%
2 287
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 620
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5511
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 913
16.6%
0 897
16.3%
. 620
11.3%
7 576
10.5%
6 509
9.2%
8 387
7.0%
5 359
 
6.5%
1 332
 
6.0%
9 325
 
5.9%
3 306
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5511
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 913
16.6%
0 897
16.3%
. 620
11.3%
7 576
10.5%
6 509
9.2%
8 387
7.0%
5 359
 
6.5%
1 332
 
6.0%
9 325
 
5.9%
3 306
 
5.6%

longitude
Text

MISSING 

Distinct597
Distinct (%)96.3%
Missing380
Missing (%)38.0%
Memory size52.5 KiB
2023-12-09T23:13:01.635761image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.896774194
Min length8

Characters and Unicode

Total characters6136
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique575 ?
Unique (%)92.7%

Sample

1st row-73.960252
2nd row-73.821595
3rd row-73.962817
4th row-73.928988
5th row-73.994509
ValueCountFrequency (%)
73.935652 3
 
0.5%
73.991034 2
 
0.3%
73.979941 2
 
0.3%
73.936906 2
 
0.3%
73.85825 2
 
0.3%
73.951958 2
 
0.3%
73.945718 2
 
0.3%
73.981771 2
 
0.3%
74.005109 2
 
0.3%
73.929345 2
 
0.3%
Other values (587) 599
96.6%
2023-12-09T23:13:02.160779image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 1000
16.3%
3 798
13.0%
9 658
10.7%
- 620
10.1%
. 620
10.1%
8 464
7.6%
4 412
6.7%
5 336
 
5.5%
6 315
 
5.1%
0 308
 
5.0%
Other values (2) 605
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4896
79.8%
Dash Punctuation 620
 
10.1%
Other Punctuation 620
 
10.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 1000
20.4%
3 798
16.3%
9 658
13.4%
8 464
9.5%
4 412
8.4%
5 336
 
6.9%
6 315
 
6.4%
0 308
 
6.3%
1 305
 
6.2%
2 300
 
6.1%
Dash Punctuation
ValueCountFrequency (%)
- 620
100.0%
Other Punctuation
ValueCountFrequency (%)
. 620
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6136
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 1000
16.3%
3 798
13.0%
9 658
10.7%
- 620
10.1%
. 620
10.1%
8 464
7.6%
4 412
6.7%
5 336
 
5.5%
6 315
 
5.1%
0 308
 
5.0%
Other values (2) 605
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6136
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 1000
16.3%
3 798
13.0%
9 658
10.7%
- 620
10.1%
. 620
10.1%
8 464
7.6%
4 412
6.7%
5 336
 
5.5%
6 315
 
5.1%
0 308
 
5.0%
Other values (2) 605
9.9%

community_board
Text

MISSING 

Distinct59
Distinct (%)9.5%
Missing380
Missing (%)38.0%
Memory size48.3 KiB
2023-12-09T23:13:02.452480image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1860
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row301
2nd row210
3rd row308
4th row304
5th row104
ValueCountFrequency (%)
105 46
 
7.4%
401 24
 
3.9%
101 23
 
3.7%
302 22
 
3.5%
413 21
 
3.4%
412 20
 
3.2%
402 19
 
3.1%
408 18
 
2.9%
104 17
 
2.7%
110 17
 
2.7%
Other values (49) 393
63.4%
2023-12-09T23:13:02.838908image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 478
25.7%
0 459
24.7%
3 247
13.3%
4 231
12.4%
2 181
 
9.7%
5 107
 
5.8%
8 52
 
2.8%
7 41
 
2.2%
6 35
 
1.9%
9 29
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1860
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 478
25.7%
0 459
24.7%
3 247
13.3%
4 231
12.4%
2 181
 
9.7%
5 107
 
5.8%
8 52
 
2.8%
7 41
 
2.2%
6 35
 
1.9%
9 29
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
Common 1860
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 478
25.7%
0 459
24.7%
3 247
13.3%
4 231
12.4%
2 181
 
9.7%
5 107
 
5.8%
8 52
 
2.8%
7 41
 
2.2%
6 35
 
1.9%
9 29
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1860
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 478
25.7%
0 459
24.7%
3 247
13.3%
4 231
12.4%
2 181
 
9.7%
5 107
 
5.8%
8 52
 
2.8%
7 41
 
2.2%
6 35
 
1.9%
9 29
 
1.6%

council_district
Text

MISSING 

Distinct51
Distinct (%)8.2%
Missing380
Missing (%)38.0%
Memory size47.6 KiB
2023-12-09T23:13:03.085984image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.729032258
Min length1

Characters and Unicode

Total characters1072
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row34
2nd row12
3rd row35
4th row34
5th row3
ValueCountFrequency (%)
3 48
 
7.7%
1 32
 
5.2%
26 27
 
4.4%
4 26
 
4.2%
33 21
 
3.4%
9 20
 
3.2%
23 20
 
3.2%
22 19
 
3.1%
35 19
 
3.1%
40 18
 
2.9%
Other values (41) 370
59.7%
2023-12-09T23:13:03.443253image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 223
20.8%
2 191
17.8%
4 164
15.3%
1 151
14.1%
9 69
 
6.4%
5 65
 
6.1%
6 64
 
6.0%
7 55
 
5.1%
0 46
 
4.3%
8 44
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1072
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 223
20.8%
2 191
17.8%
4 164
15.3%
1 151
14.1%
9 69
 
6.4%
5 65
 
6.1%
6 64
 
6.0%
7 55
 
5.1%
0 46
 
4.3%
8 44
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1072
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 223
20.8%
2 191
17.8%
4 164
15.3%
1 151
14.1%
9 69
 
6.4%
5 65
 
6.1%
6 64
 
6.0%
7 55
 
5.1%
0 46
 
4.3%
8 44
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1072
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 223
20.8%
2 191
17.8%
4 164
15.3%
1 151
14.1%
9 69
 
6.4%
5 65
 
6.1%
6 64
 
6.0%
7 55
 
5.1%
0 46
 
4.3%
8 44
 
4.1%

bin
Text

MISSING 

Distinct590
Distinct (%)96.2%
Missing387
Missing (%)38.7%
Memory size50.5 KiB
2023-12-09T23:13:03.839115image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters4291
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique568 ?
Unique (%)92.7%

Sample

1st row3397699
2nd row2093860
3rd row3027510
4th row3258681
5th row1085961
ValueCountFrequency (%)
4003539 3
 
0.5%
4005198 2
 
0.3%
3337638 2
 
0.3%
3059161 2
 
0.3%
4003108 2
 
0.3%
2097441 2
 
0.3%
1001409 2
 
0.3%
1015690 2
 
0.3%
3116055 2
 
0.3%
4061587 2
 
0.3%
Other values (580) 592
96.6%
2023-12-09T23:13:04.392410image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 737
17.2%
1 617
14.4%
3 532
12.4%
4 502
11.7%
2 426
9.9%
5 360
8.4%
9 292
 
6.8%
7 288
 
6.7%
8 279
 
6.5%
6 258
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4291
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 737
17.2%
1 617
14.4%
3 532
12.4%
4 502
11.7%
2 426
9.9%
5 360
8.4%
9 292
 
6.8%
7 288
 
6.7%
8 279
 
6.5%
6 258
 
6.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4291
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 737
17.2%
1 617
14.4%
3 532
12.4%
4 502
11.7%
2 426
9.9%
5 360
8.4%
9 292
 
6.8%
7 288
 
6.7%
8 279
 
6.5%
6 258
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4291
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 737
17.2%
1 617
14.4%
3 532
12.4%
4 502
11.7%
2 426
9.9%
5 360
8.4%
9 292
 
6.8%
7 288
 
6.7%
8 279
 
6.5%
6 258
 
6.0%

bbl
Text

MISSING 

Distinct589
Distinct (%)96.1%
Missing387
Missing (%)38.7%
Memory size52.3 KiB
2023-12-09T23:13:04.730999image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters6130
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique566 ?
Unique (%)92.3%

Sample

1st row3023937502
2nd row2051350051
3rd row3011240022
4th row3031580123
5th row1010750047
ValueCountFrequency (%)
4002810001 3
 
0.5%
1008290040 2
 
0.3%
1007840074 2
 
0.3%
4070750037 2
 
0.3%
3011970006 2
 
0.3%
3045040107 2
 
0.3%
3020230001 2
 
0.3%
3030300001 2
 
0.3%
5055150016 2
 
0.3%
2051350051 2
 
0.3%
Other values (579) 592
96.6%
2023-12-09T23:13:05.179383image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2275
37.1%
1 776
 
12.7%
3 564
 
9.2%
2 507
 
8.3%
4 494
 
8.1%
5 399
 
6.5%
7 360
 
5.9%
6 266
 
4.3%
8 247
 
4.0%
9 242
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6130
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2275
37.1%
1 776
 
12.7%
3 564
 
9.2%
2 507
 
8.3%
4 494
 
8.1%
5 399
 
6.5%
7 360
 
5.9%
6 266
 
4.3%
8 247
 
4.0%
9 242
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
Common 6130
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2275
37.1%
1 776
 
12.7%
3 564
 
9.2%
2 507
 
8.3%
4 494
 
8.1%
5 399
 
6.5%
7 360
 
5.9%
6 266
 
4.3%
8 247
 
4.0%
9 242
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6130
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2275
37.1%
1 776
 
12.7%
3 564
 
9.2%
2 507
 
8.3%
4 494
 
8.1%
5 399
 
6.5%
7 360
 
5.9%
6 266
 
4.3%
8 247
 
4.0%
9 242
 
3.9%

census_tract_2020_
Text

MISSING 

Distinct408
Distinct (%)65.8%
Missing380
Missing (%)38.0%
Memory size48.5 KiB
2023-12-09T23:13:05.702420image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.251612903
Min length1

Characters and Unicode

Total characters2016
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique278 ?
Unique (%)44.8%

Sample

1st row551
2nd row30202
3rd row203
4th row427
5th row12902
ValueCountFrequency (%)
21 8
 
1.3%
7 7
 
1.1%
109 6
 
1.0%
1903 5
 
0.8%
76 5
 
0.8%
71 5
 
0.8%
95 5
 
0.8%
1220 5
 
0.8%
37 5
 
0.8%
29102 4
 
0.6%
Other values (398) 565
91.1%
2023-12-09T23:13:06.355384image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 364
18.1%
2 280
13.9%
0 261
12.9%
3 203
10.1%
9 173
8.6%
5 173
8.6%
4 167
8.3%
7 145
 
7.2%
8 127
 
6.3%
6 123
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2016
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 364
18.1%
2 280
13.9%
0 261
12.9%
3 203
10.1%
9 173
8.6%
5 173
8.6%
4 167
8.3%
7 145
 
7.2%
8 127
 
6.3%
6 123
 
6.1%

Most occurring scripts

ValueCountFrequency (%)
Common 2016
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 364
18.1%
2 280
13.9%
0 261
12.9%
3 203
10.1%
9 173
8.6%
5 173
8.6%
4 167
8.3%
7 145
 
7.2%
8 127
 
6.3%
6 123
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2016
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 364
18.1%
2 280
13.9%
0 261
12.9%
3 203
10.1%
9 173
8.6%
5 173
8.6%
4 167
8.3%
7 145
 
7.2%
8 127
 
6.3%
6 123
 
6.1%
Distinct173
Distinct (%)27.9%
Missing380
Missing (%)38.0%
Memory size50.1 KiB
2023-12-09T23:13:06.773348image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters3720
Distinct characters18
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)5.6%

Sample

1st rowBK0102
2nd rowBX1004
3rd rowBK0801
4th rowBK0401
5th rowMN0402
ValueCountFrequency (%)
mn0502 23
 
3.7%
mn0501 22
 
3.5%
mn0101 18
 
2.9%
mn0401 10
 
1.6%
mn0201 10
 
1.6%
qn0202 9
 
1.5%
mn1001 9
 
1.5%
bk0301 9
 
1.5%
qn0201 8
 
1.3%
qn1303 8
 
1.3%
Other values (163) 494
79.7%
2023-12-09T23:13:07.306414image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1069
28.7%
1 539
14.5%
N 348
 
9.4%
2 318
 
8.5%
B 246
 
6.6%
Q 182
 
4.9%
K 180
 
4.8%
3 172
 
4.6%
M 166
 
4.5%
5 112
 
3.0%
Other values (8) 388
 
10.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2480
66.7%
Uppercase Letter 1240
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1069
43.1%
1 539
21.7%
2 318
 
12.8%
3 172
 
6.9%
5 112
 
4.5%
4 101
 
4.1%
7 51
 
2.1%
8 48
 
1.9%
6 43
 
1.7%
9 27
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
N 348
28.1%
B 246
19.8%
Q 182
14.7%
K 180
14.5%
M 166
13.4%
X 66
 
5.3%
S 26
 
2.1%
I 26
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
Common 2480
66.7%
Latin 1240
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1069
43.1%
1 539
21.7%
2 318
 
12.8%
3 172
 
6.9%
5 112
 
4.5%
4 101
 
4.1%
7 51
 
2.1%
8 48
 
1.9%
6 43
 
1.7%
9 27
 
1.1%
Latin
ValueCountFrequency (%)
N 348
28.1%
B 246
19.8%
Q 182
14.7%
K 180
14.5%
M 166
13.4%
X 66
 
5.3%
S 26
 
2.1%
I 26
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3720
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1069
28.7%
1 539
14.5%
N 348
 
9.4%
2 318
 
8.5%
B 246
 
6.6%
Q 182
 
4.9%
K 180
 
4.8%
3 172
 
4.6%
M 166
 
4.5%
5 112
 
3.0%
Other values (8) 388
 
10.4%